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Research Activity

His Web Page

Field of Study

Medical Informatics

Subject of Study

Medical Image Recognition, Neural computing, Computer aided diagnosis (medical infomatics, neural network, 医用画像認識, 3次元医用画像処理) (人間の脳の情報処理過程をコンピュータ内部でシュミレーションするニューラルコンピューティング(神経回路網計算学)の理論的研究とそのコンピューター支援画像診断システム(CADシステム)や医用画像認識への応用に関する研究)

Book / Paper

Book:

1. Tadashi Kondo :
Intelligent Decision Technologies (Eds. J.Watada et al.),
Springer-Verlag Berlin Heidelberg, May 2012.
2. Tadashi Kondo :
Neural Information Processing (Eds. M.IshiKawa et al.), pp.882-891,
Springer-Verlag Berlin Heidelberg, Berlin, Jan. 2008.
3. Tadashi Kondo and A.S. Pandya :
Knowledge-Based Intelligent Information and Engineering Systems 2004 (Eds.Mircea Gh. Negoita et al.), pp.1015-1059,
Springer-Verlag Berlin Heidelberg, Berlin, Sep. 2004.
4. Tadashi Kondo and A. S. Pandya :
Knowledge-Based Intelligent Information and Engineering Systems 2003 (Eds.V.Palade et al.), pp.849-855,
Springer-Verlag Berlin Heidelberg, Berlin, Sep. 2003.
5. H. Tamura and Tadashi Kondo :
Self-Organizing Methods in Modeling,
Marcel Fekker Inc., New York, Apr. 1984.
6. H. Tamura and Tadashi Kondo :
Uncertainty and Forecasting of Water Quality,
Springer-Verlag, Berlin, Apr. 1983.

Academic Paper (Judged Full Paper):

1. Takeshi Konishi, Tadashi Kondo, Hiroki Moriguchi, Masato Tagi and Jun Hirose :
Accelerated organ region segmentation by the revised radial basis function network using a graphics processing unit.,
The Journal of Medical Investigation : JMI, Vol.66, No.1.2, 86-92, 2019.
(Tokushima University Institutional Repository: 113295,   DOI: 10.2152/jmi.66.86,   PubMed: 31064962)
2. Shoichiro Takao, Sayaka Kondo, Junji Ueno and Tadashi Kondo :
Medical image analysis of abdominal X-ray CT images by deep multi-layered GMDH-type neural network,
Artificial Life and Robotics, Vol.23, No.2, 271-278, 2018.
(DOI: 10.1007/s10015-017-0420-z)
3. Shoichiro Takao, Sayaka Kondo, Junji Ueno and Tadashi Kondo :
Deep feedback GMDH-type neural network and its application to medical image analysis of MRI brain images,
Artificial Life and Robotics, Vol.23, No.2, 161-172, 2018.
(DOI: 10.1007/s10015-017-0410-1)
4. Shoichiro Takao, Sayaka Kondo, Junji Ueno and Tadashi Kondo :
Deep multi-layered GMDH-type neural network using revised heuristic self-organization and its application to medical image diagnosis of liver cancer,
Artificial Life and Robotics, Vol.23, No.1, 48-59, 2018.
(DOI: 10.1007/s10015-017-0392-z,   Elsevier: Scopus)
5. Tadashi Kondo, Sayaka Kondo, Junji Ueno and Shoichiro Takao :
Medical image diagnosis of kidney regions by deep feedback GMDH-type neural network using principal component-regression analysis,
Artificial Life and Robotics, Vol.22, No.1, 1-9, 2017.
(DOI: 10.1007/s10015-016-0337-y)
6. Tadashi Kondo, Junji Ueno and Shoichiro Takao :
Medical image analysis of brain X-ray CT images by deep GMDH-type neural network,
Journal of Robotics Networking and Artificial Life, Vol.3, No.1, 17-23, 2016.
(Tokushima University Institutional Repository: 112962,   DOI: 10.2991/jrnal.2016.3.1.5)
7. Tadashi Kondo, Junji Ueno and Shoichiro Takao :
Medical image diagnosis of lung cancer by deep feedback GMDH-type neural network,
Journal of Robotics Networking and Artificial Life, Vol.2, No.4, 252-257, 2016.
(Tokushima University Institutional Repository: 112961,   DOI: 10.2991/jrnal.2016.2.4.11)
8. Tadashi Kondo, Junji Ueno and Shoichiro Takao :
The 3-dimensional medical image recognition of right and left kidneys by deep GMDH-type neural network,
Journal of Bioinformatics and Neuroscience, Vol.1, No.1, 14-23, 2015.
9. Tadashi Kondo, Junji Ueno and Shoichiro Takao :
Medical image recognition of heart regions by deep multi-layered GMDH-type neural network using principal component-regression analysis,
Journal of Robotics Networking and Artificial Life, Vol.2, No.3, 166-172, 2015.
(DOI: 10.2991/jrnal.2015.2.3.7)
10. Tadashi Kondo, Junji Ueno and Shoichiro Takao :
Medical image diagnosis of liver cancer by hybrid feedback GMDH-type neural network using principal component-regression analysis,
Artificial Life and Robotics, Vol.20, No.2, 145-151, 2015.
(DOI: 10.1007/s10015-015-0213-1,   Elsevier: Scopus)
11. Tadashi Kondo, Junji Ueno and Shoichiro Takao :
Deep feedback GMDH-type neural network using principal component-regression analysis and its application to medical image recognition of abdominal multi-organs,
Journal of Robotics Networking and Artificial Life, Vol.2, No.2, 94-99, 2015.
(DOI: 10.2991/jrnal.2015.2.2.6)
12. Tadashi Kondo, Junji Ueno and Shoichiro Takao :
Logistic GMDH-type neural network using principal component-regression analysis and its application to medical image diagnosis of lung cancer,
Artificial Life and Robotics, Vol.20, No.2, 137-144, 2015.
(DOI: 10.1007/s10015-015-0200-6,   Elsevier: Scopus)
13. Tadashi Kondo, Junji Ueno and Shoichiro Takao :
Hybrid feedback GMDH-type neural network using principal component-regression analysis and its application to medical image diagnosis of lung cancer,
ICIC Express Letters, Vol.8, No.4, 1053-1060, 2014.
(Elsevier: Scopus)
14. Tadashi Kondo, Junji Ueno and Shoichiro Takao :
Medical image diagnosis of liver cancer by RBF GMDH-type neural network using principal component-regression analysis,
ICIC Express Letters, Vol.8, No.3, 1-8, 2014.
(Elsevier: Scopus)
15. Tadashi Kondo, Junji Ueno and Shoichiro Takao :
Hybrid multi-layered GMDH-type neural network using principal component regression analysis and its application to medical image diagnosis of liver cancer,
Procedia Computer Science, Vol.22, 172-181, 2013.
(DOI: 10.1016/j.procs.2013.09.093)
16. Tadashi Kondo, Junji Ueno and Shoichiro Takao :
Medical image diagnosis of lung cancer by multi-layered GMDH-type neural network self-selecting functions,
Artificial Life and Robotics, Vol.18, No.1-2, 20-26, 2013.
(DOI: 10.1007/s10015-013-0094-0,   Elsevier: Scopus)
17. Tadashi Kondo, Junji Ueno and Shoichiro Takao :
Medical image diagnosis of liver cancer by hybrid feedback GMDH-type neural network using heuristic self-organization,
ASE Science Journal, Vol.1, 12-21, 2012.
18. Tadashi Kondo, Junji Ueno and Shoichiro Takao :
Medical image diagnosis of liver cancer by feedback GMDH-type neural network using knowlege base,
Artificial Life and Robotics, Vol.17, No.3-4, 488-494, 2012.
(DOI: 10.1007/s10015-012-0090-9)
19. Tadashi Kondo and Junji Ueno :
Medical Image Diagnosis of Liver Cancer by Multi-layered GMDH-type Neural Network Using Knowlege Base,
ICIC Express Letters (ICIC-EL), Vol.6, No.4, 863-870, 2012.
20. Tadashi Kondo and Junji Ueno :
Medical Image Diagnosis of Lung Cancer by Feedback GMDH-type Neural Network Self-selecting Neural Network Architectuer,
ICIC Express Letters (ICIC-EL), Vol.6, No.3, 783-790, 2012.
(Elsevier: Scopus)
21. Tadashi Kondo and Junji Ueno :
Feedback GMDH-type Neural Network and Its Application to Medical Image Analysis of Liver Cancer,
International Journal of Innovative Computing, Information and Control, Vol.8, No.3, 2285-2300, 2012.
(Elsevier: Scopus)
22. Tadashi Kondo and Junji Ueno :
Medical image diagnosis of lung cancer by revised GMDH-type neural network using various kinds of neurons,
Artificial Life and Robotics, Vol.16, No.3, 301-306, 2011.
(DOI: 10.1007/s10015-011-0936-6)
23. Tadashi Kondo, Junji Ueno and Shoichiro Takao :
Medical image diagnosis of liver cancer using a neural network and artificial intelligence,
Journal of Advanced Computational Intelligence and Intelligent Informatics, Vol.15, No.6, 714-722, 2011.
(Elsevier: Scopus)
24. Chihiro Kondo and Tadashi Kondo :
Learning algorithm of the revised RBF network and its application to the media art system,
Artificial Life and Robotics, Vol.15, No.3, 258-263, 2010.
(DOI: 10.1007/s10015-010-0804-9)
25. Tadashi Kondo, Chihiro Kondo, Shoichiro Takao and Junji Ueno :
Feedback GMDH-type neural network algorithm and its application to medical image analysis of cancer of the liver,
Artificial Life and Robotics, Vol.15, No.3, 264-269, 2010.
(DOI: 10.1007/s10015-010-0805-8)
26. Shoichiro Takao, Toshinori Sakai, Koichi Sairyo, Tadashi Kondo, Junji Ueno, Natsuo Yasui and Hiromu Nishitani :
Radiographic comparison between male and female patients with lumbar spondylolysis.,
The Journal of Medical Investigation : JMI, Vol.57, No.1-2, 133-137, 2010.
(Tokushima University Institutional Repository: 65273,   DOI: 10.2152/jmi.57.133,   PubMed: 20299752,   CiNii: 80020865960)
27. Chihiro Kondo and Tadashi Kondo :
Revised GMDH-type neural network algorithm self-selecting optimum neural network architecture,
Artificial Life and Robotics, Vol.14, No.4, 519-523, 2009.
(DOI: 10.1007/s10015-009-0722-x)
28. Masahiro Nakagawa, Tadashi Kondo, Kudo Tsuyosi, Shoichiro Takao and Junji Ueno :
Three-dimensional medical image recognition of the cancer of the liver by a revised radial basis function (RBF) neural network algorithm,
Artificial Life and Robotics, Vol.14, No.2, 118-122, 2009.
(DOI: 10.1007/s10015-009-0640-y)
29. Chihiro Kondo, Tadashi Kondo and Junji Ueno :
Three-dimensional medical image analysis of the heart by the revised GMDH-type neural network self-selecting optimum nrural network architecture,
Artificial Life and Robotics, Vol.14, No.2, 123-128, 2009.
(DOI: 10.1007/s10015-009-0641-x)
30. Tadashi Kondo and Junji Ueno :
Medical image recognition of abdominal multi-organs by RBF GMDH-type neural network,
International Journal of Innovative Computing, Information and Control, Vol.5, No.1, 225-240, 2009.
(Elsevier: Scopus)
31. Tadashi Kondo :
Nonlinear Pattern Identification by Multi-Layered GMDH-type Neural Network Self-Selecting Optimum Neural Network Architecture,
Neural Information processing, 882-891, 2008.
(DOI: 10.1007/978-3-540-69158-7_91)
32. Tadashi Kondo and Junji Ueno :
Multi-Layered GMDH-type Neural Network Self-Selecting Optimum Neural Network Architecture and Its Application to 3-Dimensional Medical Image Recognition of Blood Vessels,
International Journal of Innovative Computing, Information and Control, Vol.4, No.1, 175-187, 2008.
(Elsevier: Scopus)
33. Tadashi Kondo, Abhijit S. Pandya and Hirofumi Nagashino :
GMDH-type Neural Network Algorithm with a Feedback Loop for Structural Identification of RBF Neural Network,
International Journal of Knowlrge-based and Intelligent Engineering Systems, Vol.11, No.3, 157-168, 2007.
(DOI: 10.3233/KES-2007-11302,   Elsevier: Scopus)
34. Tadashi Kondo and Junji Ueno :
Logistic GMDH-type Neural Network and Its Application to the Identification of the X-ray Film Characteristic Curve,
Journal of Advanced Computational Intelligence and Intelligent Informatics, Vol.11, No.3, 312-318, 2007.
35. Tadashi Kondo, Junji Ueno and Pandya S. Abhijit :
Multi-layered GMDH-type Neural Network with Radial Basis Functions and Its Application to the 3-dimensional Medical Image Recognition of the Liver,
Journal of Advanced Computational Intelligence and Intelligent Informatics, Vol.11, No.1, 96-104, 2007.
36. Tadashi Kondo and Junji Ueno :
Medical Image Recognition of the Brain by Revised GMDH-type Neural Network Algorithm with a Feedback Loop,
International Journal of Innovative Computing, Information and Control, Vol.2, No.5, 1039-1052, 2006.
37. Tadashi Kondo and Junji Ueno :
Revised GMDH-type Neural Network Algorithm with a Feedback Loop Identifying Sigmoid Function Neural Network,
International Journal of Innovative Computing, Information and Control, Vol.2, No.5, 985-996, 2006.
38. Tadashi Kondo and Junji Ueno :
Three dimensional medical image recognition of lungs by revised GMDH-type neural network algorithm,
International Journal of Computer Assisted Radiology and Surgery, Vol.1, 364-366, 2006.
(Elsevier: Scopus)
39. Tadashi Kondo, Junji Ueno and Kazuya Kondo :
Revised GMDH-type Neural Networks using AIC or PSS Criterion and Their Application to the Medical Image Recognition,
Journal of Advanced Computational Intelligence and Intelligent Informatics, Vol.9, No.3, 257-267, 2005.
40. Tadashi Kondo and Abhijit S. Pandya :
Medical Image Recognition by using the Multi-layered GMDH-type Neural Networks with the Radial Basis Function,
Intelligent Engineering System through Artificial Neural Networks, Vol.14, 785-790, 2004.
41. Tadashi Kondo and Abhijit S. Pandya :
Identification of the Radial Basis Function Networks by using the Multi-layered GMDH-type Neural Network Algorithm,
Intelligent Engineering System through Artificial Neural Networks, Vol.14, 131-136, 2004.
42. Tadashi Kondo and Abhijit S. Pandya :
Identification of the Multi-layered Neural Networks by Revised GMDH-type Neural Network Algorithm with PSS Criterion,
Lecture Notes in Computer Science, Vol.3214, 1015-1059, 2004.
(DOI: 10.1007/978-3-540-30133-2_140,   Elsevier: Scopus)
43. Tadashi Kondo :
Revised GMDH-type neural networks with radial basis functions and their application to medical image recognition of stomach,
Systems Analysis Modelling Simulation, Vol.43, No.10, 1363-1376, 2003.
(DOI: 10.1080/02329290290290024376,   Elsevier: Scopus)
44. Tadashi Kondo, Abhijit S. Pandya and T. Gilbar :
GMDH-type Neural Network Algorithm with Sigmoid Functions,
International Journal of Knowledge-Based Intelligent Engineering Systems, Vol.7, No.4, 198-205, 2003.
45. Tadashi Kondo and Abhijit S. Pandya :
Recognition of X-ray Images by Using Revised GMDH-type Neural Networks,
Lecture Notes in Computer Science, Vol.2774, 849-855, 2003.
(DOI: 10.1007/978-3-540-45226-3_116,   Elsevier: Scopus)
46. Tadashi Kondo, Abhijit S. Pandya and J. M. Zurada :
GMDH-type Neural Networks with a Feedback Loop and their Application to Nonlinear System Identification,
Intelligent Engineering System through Artificial Neural Networks, Vol.9, 117-124, 1999.
47. Tadashi Kondo :
発見的自己組織化の原理に基づいてネットワーク構造を自己組織化するGMDH-type ニューラルネットワークアルゴリズム,
Transactions of the Institute of Systems, Control and Information Engineers, Vol.11, No.4, 198-207, 1998.
48. Tadashi Kondo :
入力変数の自己選択能力を備えた非線形システム同定用ニューラルネットワーク,
Transactions of the Society of Instrument and Control Engineers, Vol.33, No.8, 825-833, 1997.
49. Tadashi Kondo :
ネットワーク構造の自己選択能力を備えたニューラルネットワークによる河川水質の非線形定常モデルの同定,
Transactions of the Institute of Systems, Control and Information Engineers, Vol.10, No.6, 277-286, 1997.
50. Tadashi Kondo :
ネットワーク構造の自己選択能力を備えたニューラルネットワークとその非線形システム同定への応用,
Transactions of the Society of Instrument and Control Engineers, Vol.31, No.12, 1978-1987, 1995.
51. Tadashi Kondo :
ニューラルネットワークを用いた広域大気汚染濃度パターンの同定,
システ制御情報学会論文誌, Vol.7, No.2, 59-67, 1994.
52. Tadashi Kondo :
ニューラルネットワークを用いた大気汚染濃度の短期予測,
Transactions of the Society of Instrument and Control Engineers, Vol.29, No.6, 710-718, 1993.
53. Tadashi Kondo :
非線形システムの同定を目的としたニューラルネットワークによる加熱炉ヒートパターンの同定,
システ制御情報学会論文誌, Vol.6, No.5, 223-232, 1993.
54. Tadashi Kondo :
回帰主成分分析を用いる多入力多出力形GMDH,
システ制御情報学会論文誌, Vol.6, No.11, 520-529, 1993.
55. Tadashi Kondo :
主成分回帰分析を用いる改良形GMDH,
システ制御情報学会論文誌, Vol.5, No.10, 391-399, 1992.
56. Tadashi Kondo :
複雑な構造をした非線形システムの同定を目的としたニューラルネットワーク,
システ制御情報学会論文誌, Vol.4, No.7, 259-266, 1991.
57. Tadashi Kondo :
非線形指数形モデルを同定する改良形GMDH,
計測自動制御学会論集, Vol.22, No.12, 1283-1289, 1986.
58. Tadashi Kondo :
モデルの次数を推定する改良形GMDH,
Transactions of the Society of Instrument and Control Engineers, Vol.22, No.9, 928-934, 1986.
59. Tadashi Kondo, 江連 久 and 安部 可治 :
数量化入力変数を用いる改良形GMDHとその圧延モデル同定への応用,
Transactions of the Society of Instrument and Control Engineers, Vol.20, No.11, 986-992, 1984.
60. K. Takaisi, Tadashi Kondo and S. MIzutame :
Statistical Analysis of Blanking Tool Wear by a Group Method of Data Handling,
Advanced Technology of Plasticity, Vol.2, 833-838, 1984.
61. Hiroyuki Tamura and Tadashi Kondo :
Heuristics Free Group Method of Data Handling Algorithm of Generating Optimal Partial Polynomials with Application to Air Pollution Prediction,
International Journal of Systems Science, Vol.11, No.9, 1095-1111, 1980.
62. 田村 坦之 and Tadashi Kondo :
改良形GMDHによる河川水質の非線形定常モデルの作成,
計測自動制御学会論集, Vol.16, No.2, 189-194, 1980.
63. 田村 坦之 and Tadashi Kondo :
: 改良形GMDHによる大気汚染のモデリングと短期予測,
Transactions of the Society of Instrument and Control Engineers, Vol.15, No.5, 622-627, 1979.
64. Tadashi Kondo and 田村 坦之 :
情報量規準AICを用いて中間表現式を自己選択する改良形GMDH,
Transactions of the Society of Instrument and Control Engineers, Vol.15, No.4, 466-471, 1979.
65. 田村 坦之 and Tadashi Kondo :
モデル選択の評価規準に予測平方和(PSS)を用いる改良形GMDH,
Transactions of the Society of Instrument and Control Engineers, Vol.14, No.5, 519-524, 1978.
66. 田村 坦之 and Tadashi Kondo :
部分表現式の次数を自己選択する改良形GMDHとその広域大気汚染濃度パターンの同定への応用,
計測自動制御学会論集, Vol.13, No.4, 351-357, 1977.

Academic Paper (Unrefereed Paper):

1. Tadashi Kondo :
Identification of the X-ray film characteristic curve by using the neural network,
Bulletin of School of Medical Sciences, the University of Tokushima, Vol.7, No.1, 9-17, 1997.
2. Tadashi Kondo :
Medical image recognition of the lungs by using the neural network,
Bulletin of School of Medical Sciences, the University of Tokushima, Vol.7, No.1, 19-26, 1997.
3. Tadashi Kondo :
改良形GMDH法によるX線フイルム特性曲線の同定,
Bulletin of School of Medical Sciences, the University of Tokushima, Vol.6, 79-84, 1996.
4. Tadashi Kondo :
神経回路網モデルによるX線CT画像を対象にした医用画像認識,
Bulletin of School of Medical Sciences, the University of Tokushima, Vol.6, 85-91, 1996.
5. Tadashi Kondo :
大規模ネットワーク構造を自己形成する神経回路網モデル,
Bulletin of School of Medical Sciences, the University of Tokushima, Vol.5, 1-11, 1995.
6. Tadashi Kondo :
医用画像認識を目的とした神経回路網モデルの開発(第1報),
Bulletin of School of Medical Sciences, the University of Tokushima, Vol.5, 13-21, 1995.
7. Tadashi Kondo :
非線形システムの同定を目的とした神経回路網モデルによる大気汚染システムのモデリング(第2報),
Bulletin of School of Medical Sciences, the University of Tokushima, Vol.4, 93-104, 1994.
8. Tadashi Kondo :
統計的非線形システム同定手法(GMDH手法)の多変量形アルゴリズム,
Bulletin of School of Medical Sciences, the University of Tokushima, Vol.4, 105-116, 1994.
9. Tadashi Kondo :
階層型ネットワーク構造をした統計的非線形システム同定手法(GMDH手法)の新しいアルゴリズム,
Bulletin of School of Medical Sciences, the University of Tokushima, Vol.3, 21-30, 1993.
10. Tadashi Kondo :
非線形システムの同定を目的とした神経回路網モデルによる大気汚染システムのモデリング,
Bulletin of School of Medical Sciences, the University of Tokushima, Vol.3, 31-40, 1993.
11. Tadashi Kondo :
非線形システムの同定を目的とした神経回路網モデルによる工学システムのモデリング,
Bulletin of School of Medical Sciences, the University of Tokushima, Vol.3, 41-51, 1993.
12. Tadashi Kondo :
神経回路網モデルを用いた非線形システムのモデリング,
Bulletin of School of Medical Sciences, the University of Tokushima, Vol.2, 9-18, 1992.
13. Tadashi Kondo :
STUDIES ON REVISED GMDH ALGORITHMS WITH APPLICATIONS,
1979.

Review, Commentary:

1. 田村 坦之 and Tadashi Kondo :
最近のGMDHの方法論と応用,
日本OR学会誌, 104-111, 1978.

Proceeding of International Conference:

1. Shoichiro Takao, Sayaka Kondo, Junji Ueno and Tadashi Kondo :
Medical image diagnosis of liver cancer by hybrid deep neural network of deep logistic GMDH-type neural network and convolutional neural network,
Proceedings of the Twenty-Third International Symposium on Artificial Life and Robotics (AROB 23rd 2018), Beppu, Jan. 2018.
2. Shoichiro Takao, Sayaka Kondo, Junji Ueno and Tadashi Kondo :
Hybrid deep neural network of deep multi-layered GMDH-type neural network and convolutional neural network and its application to medical image recognition of spleen regions,
Proceedings of the Twenty-Third International Symposium on Artificial Life and Robotics(AROB 23nd 2018), Beppu, Jan. 2018.
3. Tadashi Kondo, Sayaka Kondo, Junji Ueno and Shoichiro Takao :
Medical image diagnosis of liver cancer by deep multi-layered GMDH-type neural network using revised heuristic self-organization,
Proceedings of the Twenty-Second International Symposium on Artificial Life and Robotics(AROB 22st 2017), Beppu, Jan. 2017.
4. Tadashi Kondo, Sayaka Kondo, Junji Ueno and Shoichiro Takao :
Medical image diagnosis of lung cancer by deep logistic GMDH-type neural network using revised heuristic self-organization,
Proceedings of the Twenty-Second International Symposium on Artificial Life and Robotics(AROB 22st 2017), Beppu, Jan. 2017.
5. Tadashi Kondo, Junji Ueno and Shoichiro Takao :
Medical image analysis of brain X-ray CT images by deep GMDH-type neural network,
The proceedings of the 2016 International Conference on Artificial Life and Robotics (ICAROB 2016), 120-124, Okinawa, Jan. 2016.
6. Tadashi Kondo, Junji Ueno and Shoichiro Takao :
Medical image diagnosis of lung cancer by deep feedback GMDH-type neural network,
The proceedings of the 2016 International Conference on Artificial Life and Robotics (ICAROB 2016), 125-129, Okinawa, Jan. 2016.
7. Tadashi Kondo, Junji Ueno and Shoichiro Takao :
Medical image analysis of abdominal X-ray CT images by deep multi-layered GMDH-type neural network,
Proceedings of the Twenty-First International Symposium on Artificial Life and Robotics (AROB 21st 2016), 237-240, Beppu, Jan. 2016.
8. Tadashi Kondo, Junji Ueno and Shoichiro Takao :
Deep feedback GMDH-type neural network and its application to medical image analysis of MRI brain images,
Proceedings of the Twenty-First International Symposium on Artificial Life and Robotics (AROB 21st 2016), 233-236, Beppu, Jan. 2016.
9. Tadashi Kondo, Junji Ueno and Shoichiro Takao :
The 3-dimensional medical image recognition of right and left kidneys by deep GMDH-type neural network,
Proceedings of International Conference on Intelligent Informatics and Biomedical Sciences, 313-320, Okinawa, Dec. 2015.
10. Tadashi Kondo, Junji Ueno and Shoichiro Takao :
Medical image analysis of MRI brain images by deep RBF GMDH-type neural network using principal component-regression analysis,
Proceedings of 2015 IIAI 4th international congress on advanced informatics, 586-592, Okayama, Jul. 2015.
(DOI: 10.1109/IIAI-AAI.2015.249)
11. Tadashi Kondo, Junji Ueno and Shoichiro Takao :
Medical image diagnosis of kidney regions by deep feedback GMDH-type neural network using principal component-regression analysis,
Proceedings of the twentieth international symposium on artificial life and robotics 2015, 424-427, Beppu, Jan. 2015.
12. Tadashi Kondo, Junji Ueno and Shoichiro Takao :
Deep multi-layered GMDH-type neural network using principal component-regression analysis and its application to medical image recognition of brain and blood vessels,
Proceedings of the twentieth international symposium on aritificial life and robotics 2015, 92-95, Beppu, Jan. 2015.
13. Tadashi Kondo, Junji Ueno and Shoichiro Takao :
Medical image recognition of heart regions by deep multi-layered GMDH-type neural network using principal component-regression analysis,
The proceedings of international conference on artificial life and robotics (ICAROB 2015), 115-118, Oita, Jan. 2015.
14. Tadashi Kondo, Junji Ueno and Shoichiro Takao :
Deep feedback GMDH-type neural network using principal component-regression analysis and its application to medical image recognition of abdominal multi-organs,
The proceedings of international conference on artificial life and robotics (ICAROB 2015), 119-122, Oita, Jan. 2015.
15. Tadashi Kondo, Junji Ueno and Shoichiro Takao :
Medical image recognition of abdominal multi-organs by hybrid multi-layered GMDH-type neural network using principal component-regression analysis,
Proceedings of 2014 second international symposium on computing and networking, 157-163, Matuyama, Dec. 2014.
16. Tadashi Kondo, Junji Ueno and Shoichiro Takao :
Hybrid feedback GMDH-type neural network using principal component-regression analysis and its application to medical image recognition of heart regions,
Proceedings of inetrnational conference of SCIS and ISIS 2014, 1203-1208, kitakyushu, Dec. 2014.
17. Tadashi Kondo, Junji Ueno and Shoichiro Takao :
Logistic GMDH-type neural network using principal component-regression analysis and its application to medical image diagnosis of lung cancer,
Proceedings of the nineteenth international symposium on artificial life and robotics, 335-338, Beppu, Jan. 2014.
18. Tadashi Kondo, Junji Ueno and Shoichiro Takao :
Medical image diagnosis of liver cancer by hybrid feedback GMDH-type neural network using principal component-regression analysis,
Proceedings of the nineteenth international symposium on artificial life and robotics, 339-342, Beppu, Jan. 2014.
19. Tadashi Kondo, Junji Ueno and Shoichiro Takao :
Feedback RBF GMDH-type neural network using principal component-regression analysis and its application to medical image diagnosis of lung cancer,
Proceedings of the first international symposium on computing and networking, 155-161, Matsuyama, Dec. 2013.
20. Tadashi Kondo, Junji Ueno and Shoichiro Takao :
Hybrid multi-layered GMDH-type neural network using principal component regression analysis and its application to medical image diagnosis of liver cancer,
Proceedings of 17th international conference in knowledge based and intelligent information and engineering systems, 39-48, Kitakyushu, Sep. 2013.
21. Tadashi Kondo, Junji Ueno and Shoichiro Takao :
Hybrid feedback GMDH-type neural network using principal component-regression analysis and its application to medical image diagnosis of lung cancer,
Proceedings of the eighth international conference of the innovative computing, information and control (ICICIC2013), 1-8, Kumamoto, Sep. 2013.
22. Tadashi Kondo, Junji Ueno and Shoichiro Takao :
Medical image diagnosis of liver cancer by RBF GMDH-type neural network using principal component-regression analysis,
Proceedings of the eighth international conference of the innovative computing, information and control (ICICIC2013), 1-8, Kumamoto, Sep. 2013.
23. Tadashi Kondo, Junji Ueno and Shoichiro Takao :
Multi-layered GMDH-type neural network algorithm using principal component-regression analysis and PSS criterion,
Proceedings of the 44th ISCIE International Symposium on Stochastic Systems Theory and Its Applications, 273-278, Tokyo, Jun. 2013.
24. Tadashi Kondo, Junji Ueno and Shoichiro Takao :
Medical image diagnosis of liver cancer by multi-layered GMDH-type neural network using principal component-regression analysis and PSS criterion,
Proceedings of the 44th ISCIE International Symposium on Stochastic Systems Theory and Its Applications, 255-262, Tokyo, Jun. 2013.
25. Tadashi Kondo, Junji Ueno and Shoichiro Takao :
Hybrid multi-layered GMDH-type neural network using principal component-regression analysis and its application to medical image diagnosis of lung cancer,
Proceedings of 2012 ASE International Conference on BioMedical Computing, 575-582, Washington D. C., Dec. 2012.
26. Tadashi Kondo, Junji Ueno and Shoichiro Takao :
Hybrid feedback GMDH-type neural network self-selecting various neurons and its application to medical image diagnosis of lung cancer,
Proceedings of international conference SCIS-ISIS 2012, 1925-1930, Kobe, Nov. 2012.
27. Tadashi Kondo, Junji Ueno and Shoichiro Takao :
Hybrid multi-layered GMDH-type neural network self-selecting various neurons and its application to medical image diagnosis of liver cancer,
Proceedings of international conference SCIS-ISIS 2012, 1919-1924, Kobe, Nov. 2012.
28. Tadashi Kondo, Junji Ueno and Shoichiro Takao :
Medical image diagnosis of liver cancer by multi-layered GMDH-type neural network using principal component-regression analysis and PSS criterion,
Abstracts of the 44th ISCIE international sysmposium on stochastic systems theory and its applications, 119-120, Tokyo, Nov. 2012.
29. Tadashi Kondo, Junji Ueno and Shoichiro Takao :
Multi-layered GMDH-type neural network algorithm using principal component-regression analysis and PSS criterion,
Abstracts of the 44th ISCIE international symposium on stochastic systems theory and its applications, 73-74, Tokyo, Nov. 2012.
30. Tadashi Kondo, Junji Ueno and Shoichiro Takao :
Medical image diagnosis of liver cancer by revised GMDH-type neural network using feedback loop calculation,
Proceedings of 2012 sixth international conference on genetic and evolutionary computing, 237-240, Kitakyushu, Aug. 2012.
31. Tadashi Kondo, Junji Ueno and Shoichiro Takao :
Feedback GMDH-type neural network self-selecting various functions and its application to medical image diagnosis of lung cancer,
Proceedings of 13th ACIS international conference on sofutware engineering, artificial intelligence, networking and parallel distrivuted computing (SNPD2012), 203-208, Kyoto, Aug. 2012.
32. Tadashi Kondo, Junji Ueno and Shoichiro Takao :
Medical image diagnosis of lung cancer by hybrid multi-layered GMDH-type neural network using knowlege base,
Proceedings of the 2012 International Conference on Complex Medical Engineering, 663-668, Kobe, Jul. 2012.
33. Tadashi Kondo, Junji Ueno and Shoichiro Takao :
A new multi-layered GMDH-type neural network algorithm using principal component-regression analysis,
Proceedings of the 43th ISCIE International Symposium on Stochastic Systems Theory and Its Applications, 1-6, Shiga, Jul. 2012.
34. Tadashi Kondo, Junji Ueno and Shoichiro Takao :
Medical image diagnosis of liver cancer by multi-layered GMDH-type neural network using artificial intelligence technology,
Proceedings of the 43th ISCIE International Symposium on Stochastic Systems Theory and its Applications, 1-6, Shiga, Jul. 2012.
35. Tadashi Kondo, Junji Ueno and Shoichiro Takao :
Feedback GMDH-type neural network algorithm using prediction error criterion defined as AIC,
Proceedings of the 4th international conference on intelligent decision technologies, 313-322, Gifu, May 2012.
36. Tadashi Kondo, Junji Ueno and Shoichiro Takao :
Medical image diagnosis of lung cancer by multi-layered GMDH-type neural network self-selecting functions,
Proceedings of the seventeenth International Symposium on Artificial Life and Robotics 2012, 1009-1012, Beppu, Jan. 2012.
37. Tadashi Kondo, Junji Ueno and Shoichiro Takao :
Medical image diagnosis of liver cancer by feedback GMDH-type neural network using knowlege base,
Proceedings of the seventeenth International Symposium on Artificial Life and Robotics 2012, 1021-1024, Beppu, Jan. 2012.
38. Tadashi Kondo, Junji Ueno and Shoichiro Takao :
Hybrid GMDH-type neural network using artificial intelligence and its application to medical image diagnosis of liver cancer,
Proceedings of 2011 IEEE/SICE International Symposium on System Integration, 1101-1106, Kyoto, Dec. 2011.
(DOI: 10.1109/SII.2011.6147603,   Elsevier: Scopus)
39. Tadashi Kondo, Junji Ueno and Shoichiro Takao :
Medical image diagnosis of lung cancer by revised GMDH-type neural network self-selecting optimum neuron architectuers,
Proceedings of 2011 IEEE/SICE International Symposium on System Integration, 1107-1112, Kyoto, Dec. 2011.
(DOI: 10.1109/SII.2011.6147604,   Elsevier: Scopus)
40. Tadashi Kondo and Junji Ueno :
Medical Image Diagnosis of Liver Cancer by Multi-layered GMDH-type Neural Network Using Artificial Intelligence Technology,
Abstracts of the 43rd ISCIE international symposium on stochastic systems theory and its applications, 32-33, Shiga, Oct. 2011.
41. Tadashi Kondo and Junji Ueno :
A New Multi-layered GMDH-type Neural Network Algorithm Using Principal Component-Regression Analysis,
Abstracts of the 43rd ISCIE international sysmposium on Stochastic systems theory and its applications, 30-31, Shiga, Oct. 2011.
42. Shoichiro Takao, Koichi Sairyo, Tadashi Kondo, Junji Ueno, Natsuo Yasui and Hiromu Nishitani :
Lumbar spondylolysis: clinical significance of gender difference,
International Skeletal Society 2011 Annual Meeting, San Diego, Sep. 2011.
43. Tadashi Kondo and Junji Ueno :
Medical image diagnosis of lung cancer by revised GMDH-type neural network using heuristic self-organization,
Proceedings of SICE annual concerence 2011, 1254-1259, Tokyo, Sep. 2011.
44. Tadashi Kondo and Junji Ueno :
Revised GMDH-type neural network using principal component-regression analysis,
Proceedings of SICE annual conference 2011, 1248-1253, Tokyo, Sep. 2011.
45. Tadashi Kondo and Junji Ueno :
Fedback GMDH-type neural network and Its application to medical image analysis of liver cancer,
Proceedings of the 42th ISCIE Inernational Symposium on Stochastic Systems Theory and Its Applications, 256-263, Okayama, Jun. 2011.
46. Tadashi Kondo :
Revised GMDH-type neural network using artificial intelligence and Its application to medical image diagnosis,
Proceedings of 2011 IEEE Symposium Series on Computational Intelligence, 76-83, PARIS, FRANCE, Apr. 2011.
(DOI: 10.1109/HIMA.2011.5953960,   Elsevier: Scopus)
47. Tadashi Kondo and Junji Ueno :
Medical image diagnosis of lung cancer by revised GMDH-type neural network using various kinds of neurons,
Proceedings of the sixteenth International Symposium on Artificial Life and Robotics 2011, 866-869, Beppu, Jan. 2011.
48. Tadashi Kondo, Junji Ueno and Shoichiro Takao :
Medical image diagnosis of liver cancer by revised GMDH-type neural network using knowledge base,
Proceedings of International Forum on Medical Imaging in Asia 2011, 1-7, Naha, Jan. 2011.
49. Tadashi Kondo and Junji Ueno :
Medical image diagnosis of liver cancer using multi-layered GMDH-type neural network,
Proceedings of Joint 5th International Conference on Soft Computing and Intelligent Systems and 11th International Symposium on Advanced Intelligent Systems, 446-451, Okayama, Dec. 2010.
50. Tadashi Kondo and Junji Ueno :
Feedback GMDH-type neural network and its application to medical image analysis of the liver cancer,
Abstracts of the 42th ISCIE international symposium on stochastic systems theory and its applications, 81-82, Okayama, Nov. 2010.
51. Tadashi Kondo, Junji Ueno and Shoichiro Takao :
Medical image diagnosis of liver cancer using neural natwork and artificial intelligence,
Proceedings of the 2010 International Symposium on Intelligent Systems, No.S6-8-3, 1-6, Tokyo, Sep. 2010.
52. Tadashi Kondo and Junji Ueno :
Nonliear system identification by feedback GMDH-type neural network with architecture self-selecting function,
Proceedings of 2010IEEE Multi-Conference on System and Control, 1521-1526, Yokohama, Sep. 2010.
(DOI: 10.1109/ISIC.2010.5612889,   Elsevier: Scopus)
53. Tadashi Kondo, Masahiro Nakagawa, Shoichiro Takao and Junji Ueno :
Medical image recognition of cancer of the liver by GMDH-type neural network,
Proceedings of the 41th International Symposium on Stochastic Systems Theory and Its Applications, 81-86, Kobe, Jun. 2010.
54. Masahiro Nakagawa, Tadashi Kondo, Shoichiro Takao and Junji Ueno :
Three-dimensional medical image recognition of the lung by the revised radial basis function (RBF) network algorithm,
Proceedings of the 41th ISCIE International Symposium on Stochastic Systems Theory and Its Applications, 75-80, Kobe, Jun. 2010.
55. Chihiro Kondo and Tadashi Kondo :
Identification of the interactive art system using the revised RBF network,
Proceedings of the 41th ISCIE International Symposium on Stochastic Systems Theory and Its Applications, 63-68, Kobe, Jun. 2010.
56. Chihiro Kondo and Tadashi Kondo :
Learning algorithm of the revised RBF network and its application to the media art system,
The Fifteenth International Symposium on Artificial Life and Robotics 2010, 786-789, Beppu, Feb. 2010.
57. Chihiro Kondo, Tadashi Kondo and Junji Ueno :
Feedback GMDH-type neural network algorithm and its application to medical image analysis of cancer of the liver,
The Fifteenth International Symposium on Artificial Life and Robotics 2010, 790-793, Beppu, Feb. 2010.
58. Masahiro Nakagawa, Tadashi Kondo, Shoichiro Takao and Junji Ueno :
3-dimensional medical image recognition of the lung by the revised radial basis function (RBF) neural network algorithm,
Abstracts of the 41st ISCIE International Symposium on Stochastic Systems Theory and Its Applications, 37-38, Nov. 2009.
59. Tadashi Kondo, Masahiro Nakagawa, Shoichiro Takao and Junji Ueno :
Medical image recognition of cancer of the liver by GMDH-type neural network,
Abstract of the 41st ISCIE International Symposium on Stochastic Systems Theory and Its Applications, 39-40, Nov. 2009.
60. Chihiro Kondo and Tadashi Kondo :
Identification of the interactive art system using the revised RBF network,
Abstract of the 41st ISCIE International Symposium on Stochastic Systems Theory and Its Applications, 33-34, Nov. 2009.
61. Chihiro Kondo and Tadashi Kondo :
Three-dimensional medical image recognition of the heart by revised GMDH-type neural network algorithm,
ICROS-SICE International Joint Conference 2009, 2504-2509, Aug. 2009.
62. Chihiro Kondo and Tadashi Kondo :
Revised RBF network algorithm and its application to the interactive art system,
ICROS-SICE International Joint Conference 2009, 4526-4529, Aug. 2009.
63. Tsuyosi Kudo, Tadashi Kondo, Masahiro Nakagawa and Junji Ueno :
Medical image recognition of the white and gray matters of the brain by radial basis function (RBF) neural network,
Proceedings of the 40th ISCIE International Symposium on Stochastic Systems Theory and Its Applications, 259-263, Jun. 2009.
64. Masahiro Nakagawa, Tadashi Kondo, Tsuyosi Kudo, Shoichiro Takao and Junji Ueno :
Three-dimensional medical image recognition of the cancer of the liver by artificial neural network,
Proceedings of the 40th ISCIE International Symposium on Stochastic Systems Theory and Its Applications, 171-175, Jun. 2009.
65. Tadashi Kondo and Junji Ueno :
Revised GMDH-type neural network algorithm for medical image recognition and its application to 3-dimensional medical image analysis of the heart,
Proceedings of the 40th ISCIE International Symposium on Stochastic Systems Theory and Its Applications, 148-153, Jun. 2009.
66. Masahiro Nakagawa, Tadashi Kondo, Tsuyosi Kudo, Shoichiro Takao and Junji Ueno :
Three-dimensional medical image recognition of cancer of the liver by the revised radial basis function (RBF) neural network algorithm,
The Fourteenth International Symposium on Artificial Life and Robotics 2009, 385-388, Feb. 2009.
67. Chihiro Kondo and Tadashi Kondo :
Three-dimensional medical image analysis of the heart by the revised GMDH-type neural network self-selecting optimum neural network architecture,
The Fourteenth International Symposium on Artificial Life and Robotics 2009, 397-400, Feb. 2009.
68. Chihiro Kondo and Tadashi Kondo :
Revised GMDH-type neural network algorithm self-selecting optimum neural network architecture,
The Fourteenth International Symposium on Artificial Life and Robotics 2009, 410-413, Feb. 2009.
69. Tsuyoshi Kudo, Tadashi Kondo, Masahiro Nakagawa and Junji Ueno :
Medical image recognition of the white and gray matters of the brain by radial basis function (RBF) neural network,
Abstracs of the 40th ISCIE International Symposium on Stochastic Systems Theory and Its Applications, 19-20, Nov. 2008.
70. Tadashi Kondo and Junji Ueno :
Revised GMDH-type neural network algorithm for medical image recognition and its application to 3-demensional medical image analysis of the heart,
Abstracts of the 40th ISCIE International Symposium on Stochastic Systems Theory and Its Applications, 41-42, Nov. 2008.
71. Masahiro Nakagawa, Tadashi Kondo, Tsuyoshi Kudo and Junji Ueno :
Three-dimensional medical image recognition of cancer of the liver by artificial neural network,
Abstracts of the 40th ISCIE International Symposium on Stochastic Systems Theory and Its Applications, 87-88, Nov. 2008.
72. Tadashi Kondo :
Feedback GMDH-type neural network algorithm using prediction error criterion for self-organization,
SICE Annual Conference 2008, 1044-1049, Aug. 2008.
73. Tadashi Kondo :
Feedback GMDH-type neural network using prediction error criterion and its application to 3-dimensional medical image recognition,
SICE Annual Conference 2008, 1050-1055, Aug. 2008.
74. Takaomi Matuki, Tadashi Kondo, Tsuyosi Kudo, Atusi Itami, Masahiro Nakagawa and Yusuke Matumura :
Recognition of 3-dimensional medical images of the lungs, pulmonary vessels andf bronchial trees by artificial neural networks,
Proceedings of the 39th ISCIE International Symposimum In Stochastic Systems Theory and Its Applications, 201-206, Jun. 2008.
75. Tsuyosi Kudo, Tadashi Kondo, Takaomi Matuki, Atusi Itami, Masahiro Nakagawa and Yusuke Matumura :
Recognition of 3-dimensional medical images of the head by radial basis function (RBF) neural network,
Proceedings of the 39th ISCIE International Symposium In Stochastic Systems Theory and Its Applications, 207-212, Jun. 2008.
76. Tadashi Kondo and Junji Ueno :
Medical Image Recognition of Abdominal Organs by RBF GMDH-type Neural Network,
Proceedings of the 39th ISCIE International Symposium In Stochastic Systems Theory and Its Applications, 177-182, Jun. 2008.
77. Tsuyosi Kudo, Tadashi Kondo, Takaomi Matuki, Atusi Itami and Masahiro Nakagawa :
Recognition of 3-dimensional medical images of the head by radial basis function (RBF) neural network,
Abstracts of the 39th ISCIE International symposium on Stochastic Systems Theory and Its Applications, 72-73, SAGA, Nov. 2007.
78. Takaomi Matuki, Tadashi Kondo, Tsuyosi Kudo, Atusi Itami and Masahiro Nakagawa :
Recognition of 3-dimensional medical images of the lungs, pulmonary vessels and bronchial trees by artificial neural networks,
Abstract of the 39th ISCIE International Symposium on Stochastic Systems Theory and Its Applications, 70-71, SAGA, Nov. 2007.
79. Tadashi Kondo and Junji Ueno :
Medical image recognition of abdominal organs by RBF GMDH-type neural network,
Abstract of the 39th ISCIE International Symposium on Stochastic Systems Theory and Applications, 56-57, SAGA, Nov. 2007.
80. Tadashi Kondo and Junji Ueno :
Feedback GMDH-type Neural Network Self-Selecting Optimum Neural Network Architecture and Its Application to 3-Dimensional medical Image Recognition of the Lungs,
Proceedings of international Workshop on Inductive Modeling 2007, 63-70, Sep. 2007.
81. Tadashi Kondo and Junji Ueno :
Multi-Layered GMDH-type Neural Network Self-selecting Optimum Neural Network Atcbitrcture and Its Application to Nonlinear System Identification,
Proceedings of international Workshop on Inductive Modeling 2007, 55-62, Sep. 2007.
82. Matuki Takaomi, Kudo Tsuyoshi, Tadashi Kondo and Junji Ueno :
Three dimensional medical images of the lungs and brain recognized by artificial neural networks,
Proceedings of SICE annual Conference 2007, 1117-1121, Sep. 2007.
83. Tadashi Kondo and Junji Ueno :
Medical Image Recognition of Abdominal X-ray CT Images by RBF GMDH-type Neural Network,
Proceedings of SICE annual Conference 2007, 1112-1116, Sep. 2007.
84. Tadashi Kondo :
Three-Dimensional medical Image Recognition of Blood Vessels by Multi-Layered GMDH-Type Neural Network Self-Selecting Optimum Neural Network Archtecture,
Proceedings of the 38th ISCIE international symposium on stochastic sytems theory and its applications, 46-51, Jun. 2007.
85. Matuki Takaomi, Tadashi Kondo and Junji Ueno :
Three dimensional medical image recognition of the lungs using artificial neural network,
Proceedings of International Symposium on Artificial Life and Robotics, No.PS3, 1-2, Jan. 2007.
86. Tadashi Kondo and Junji Ueno :
Three dimensional medical image recognition of the brain by feedback GMDH-type neural network self-selecting optimum neural network architecture,
Proceedings of International Symposium on Artificial Life and Robotics, No.GS20-2, 1-4, Jan. 2007.
87. Tadashi Kondo and Junji Ueno :
Feedback GMDH-type neural network algorithm self-selecting optimum neural network architecture,
Proceedings of International Symposium on Artificial Life and Robotics, No.GS21-4, 1-4, Jan. 2007.
88. Tadashi Kondo :
Three-dimensional medical image recognition of blood vessels by multi-layered GMDH-type neural network self-selecting optimum neural network architecture,
Abstract of the 38th International Symposium on Stochastic Systems Theory and Its Applications, 19-20, Suwa, Nov. 2006.
89. Tadashi Kondo :
A new multi-layered GMDH-type neural network self-selecting optimum neural network architecture,
Abstract of the 38th International Symposium on Stochastic Systems Theory and Its Applications, 17-18, Suwa, Nov. 2006.
90. Tadashi Kondo :
A New Algorithm of Multi-Layered Neural Network Using Heuristic Self-Organization,
Proceedings of 17th International Symposium on Mathematical Theory of Networks and Systems, 911-916, Jul. 2006.
91. Tadashi Kondo :
Medical Image Recognition by Revised GMDH-type Neural Network Algorithm with a Feedback Loop Identifying Sigmoid Function Neural Network,
Proceedings of the 37th ISCIE International Symposium on Stochastic Systems Theory and Its Applications, 143-148, Jun. 2006.
92. Tadashi Kondo :
Revised GMDH-type Neural Network Algorithm with a Feedback Loop Identifying Sigmoid Function Neural Network,
Proceedings of the 37th ISCIE International Aymposium on Stochastic Systems Theory and Its Applications, 137-142, Jun. 2006.
93. Tadashi Kondo :
Medical Image Recognition by Revised GMDH-type Neural Network Algorithm with a Feedback Loop Identifying Sigmoid Function Neural Network,
Abstracts of the 37th ISCIE international symposium on stochastic systems theory and its applications, 56-57, Oct. 2005.
94. Tadashi Kondo :
Revised GMDH-type Neural Network Algorithm with a Feedback Loop Identifying Sigmoid Function Neural Network,
Abstracts of the 37th ISCIE international symposium on stochastic systems theory and its applications, 54-55, Oct. 2005.
95. Tadashi Kondo, Junji Ueno, Kazuya Kondo and Abhijit S. Pandya :
An application of self-selecting algorithm for optimum neural network architecture to medical image recognition,
Proceeding of the 44th SICE annual conference, 1657-1661, Aug. 2005.
96. Tadashi Kondo, Junji Ueno, Kazuya Kondo and Abhijit S. Pandya :
An algorithm for self-selecting optimum neural network architecture,
Proceeding of the 44th SICE annual conference, 1645-1650, Aug. 2005.
97. Tadashi Kondo :
Medical image recognition by using the revised GMDH-type neural networks self-selectiong the optimum neural network architecture,
Proceedings of the first international conference on complex medical engineering CME2005, 412-417, May 2005.
98. Tadashi Kondo and Abhijit S. Pandya :
Identification of the Multi-layered Neural Networks by Revised GMDH-type Neural Network Algorithm with PSS Criterion,
Knowledge-based intelligent information engineering systems and allied technologies, 1051-1059, Sep. 2004.
99. Tadashi Kondo :
Revised GMDH-type Neural Networks using Prediction Error Criterions AIC and PSS,
Proceeding of the Joint 2nd International Conference on Soft Computing and Intelligent Systems and 5th International Symposium on Advanced Intelligent System, 1-6, Sep. 2004.
100. Tadashi Kondo :
Revised GMDH-type Neural Networks using PSS Criterion,
Proceeding of the 47th IEEE International Midwest Symposium on Circuits and System, 81-84, Jul. 2004.
(Elsevier: Scopus)
101. Tadashi Kondo and Abhijit S. Pandya :
Recognition of X-ray CT images by using revised GMDH-type neural networks,
Knowledge-based intelligent information engineering systems and allied technologies, 849-855, Sep. 2003.
102. Tadashi Kondo :
Structural Identification of the Multi-layered Neural Networks by using Revised GMDH-type Neural Network Algorithm with a Feedback Loop,
Proceeding of the SICE Annual Conference 2003, International Session Papers, 2806-2811, Aug. 2003.
103. Tadashi Kondo and Abhijit S. Pandya :
Modeling of X-ray CT Image by using Revised GMDH-type Neural Networks with Sigmoid Functions,
Proc. of IEEE International Symposium on Computational Intelligence in Robotics and Automation, 1180-1185, Jul. 2003.
(DOI: 10.1109/CIRA.2003.1222164,   Elsevier: Scopus)
104. Tadashi Kondo and Abhijit S. Pandya :
Revised GMDH-type neural networks with a feedback loop and their application to the medical image recognition,
Proceeding of the 9th International Conference on Neural Information Processing, No.1415, 1-6, Aug. 2002.
105. Tadashi Kondo :
Identification of radial basis function networks by using revised GMDH-type neural networks with a feedback loop,
Proceeding of the SICE Annual Conference 2002, International Session Papers, 2882-2887, Aug. 2002.
106. S Mehta, Tadashi Kondo and Abhijit S. Pandya :
GMDH Algorithms for Modeling Systems in Noisy Envitonment,
The 6th World Multiconference on Systems, Cybernetics and Informatics, 14-18, Florida, Jul. 2002.
107. Tadashi Kondo, Abhijit S. Pandya and T Gilbar :
Structural identification of the multi-layered neural networks by using GMDH-type neural network algorithm,
Knowledge-based intelligent information engineering systems and allied technologies, 89-94, Sep. 2001.
108. Tadashi Kondo and Abhijit S. Pandya :
Medical image recognition by using logistic GMDH-type neural networks,
Proceedings of the 40th SICE annual conference, international session papers, No.313A-2, 1-6, Jul. 2001.
109. Tadashi Kondo and Abhijit S. Pandya :
Medical image recognition by using GMDH-type neural networks with sigmoid functions,
Proceedings of the international technical conference on circuits and systems, computers and communications, 1118-1121, Jul. 2001.
110. Tadashi Kondo :
Revised GMDH-type neural networks with radial basis functions and their application to medical image recognition of stomach,
Proceeding of the 15th European simulation multiconference, Modeling and simulation 2001,, 673-679, Jun. 2001.
111. Tadashi Kondo :
GMDH-type Neural Networks with a Feedback Loop and their Application to the Identification of the Large-spatial Air Pollution Pattern,
Proceeding of the 39th SICE Annual Conference International Session Papers, No.112A-4, 1-6, Jul. 2000.
112. Tadashi Kondo and Abhijit S. Pandya :
GMDH-type Neural networks using the Radial Basis Function and their Application to the Medical Image Recognition of the Brain,
Proceeding of the 39th SICE Annual Conference International Session Papers, No.313A-2, 1-6, Jul. 2000.
113. Abhijit S. Pandya, Tadashi Kondo, Amit Talati and Suryaprasad Jayadevappa :
Foreign currency rate forecasting using neural networks,
Proceedings of SPIE, Vol.4055, 392-400, Orlando, Apr. 2000.
(Elsevier: Scopus)
114. Tadashi Kondo, Abhijit S. Pandya and J. M. Zurada :
GMDH-type Neural Networks and their Application to the Medical Image Recognition of the Lungs,
Proceedings of 38th SICE Annual Conference International Session Papers, 1181-1186, Jul. 1999.
115. Abhijit S. Pandya, Tadashi Kondo, Trupti U. Shah and Viraf R. Gandhi :
Prediction of Stock Market Characteristics Using Neural Networks,
Proceedings of SPIE, Vol.3722, 189-197, Orlando, Mar. 1999.
116. Tadashi Kondo, Abhijit S. Pandya and J. M. Zurada :
Logistic GMDH-type Neural Networks and their Application to the Identification of the X-ray Film Characteristic Curves,
Proceedings of IEEE International Conference on Systems, Man and Cybernetics, 437-442, 1999.
117. Tadashi Kondo :
GMDH Neural Network Algorithm using the Heuristic Self-Organization Method and Its Application to the Pattern Identification Problem,
Proceedings of 37th SICE Annual Conference International Session Papers, 1143-1148, Jul. 1998.
118. Tadashi Kondo :
GMDH neural network using the heuristic self-organization method and its application to the medical image recognition,
Researches of Biological Functions for New Technologies, 21-22, 1998.
119. Tadashi Kondo :
The Learning Algorithms of the GMDH Neural Network and their Application to the Medical Image Recognition,
Proceedings of 37th SICE Annual Conference International Session Papers, 1109-1114, 1998.
120. H. Tamura and Tadashi Kondo :
Nonlinear Modeling for Short-Term Prediction of Air Pollution Concentration by a Revised GMDH,
Proc. Int. Conf. on Cybernetics and Society, IEEE Syst., Man, Cybern Society, 596-601, 1978.
121. H. Tamura and Tadashi Kondo :
Large-Spatial pattern Identification of Air Pollution by A Combined Model of Source-Receptor Matrix and Revised GMDH,
Proc. IFAC Sympo. on Environmental Systems Planning, Design and Control, 373-380, 1977.

Proceeding of Domestic Conference:

1. Shoichiro Takao, 近藤 明佳, Junji Ueno and Tadashi Kondo :
ディープ多層構造型GMDH-typeニューラルネットワークを用いた肝臓がんの医用画像診断,
医療情報学会・人工知能学会AIM合同研究会資料SIG-AIMED-004-03, No.004-03, 1-6, Nov. 2017.
2. Shoichiro Takao, 近藤 明佳, Junji Ueno and Tadashi Kondo :
ディープ多層構造型GMDH-typeニューラルネットワークを用いた肺がんの医用画像診断,
第31回人工知能学会全国大会論文集, No.2J4-2in1, 1-4, Jun. 2017.
3. Tadashi Kondo, Junji Ueno and Shoichiro Takao :
人工知能技術を用いたX線CT画像を対象にした医用画像診断支援システム,
IEICE Technical Report, Vol.IBISML2013-11, 75-80, Jul. 2013.
4. Tadashi Kondo, Junji Ueno and Shoichiro Takao :
Multi-layered GMDH-type neural network using Prediction Sum of Square (PSS) and its application to medical image diagnosis of liver cancer,
IEICE Technical Report, Vol.IE2013-7, 35-40, Apr. 2013.
(CiNii: 40019645679)
5. Tadashi Kondo, Junji Ueno and Shoichiro Takao :
Multi-layered GMDH-type neural network algorithm using Prediction Sum ofSquares(PSS)criterion and its applicationt ononlinear system identification,
IEICE Technical Report, Vol.KBSE2012-64, 35-40, Jan. 2013.
(CiNii: 110009728167)
6. Tadashi Kondo, Junji Ueno and Shoichiro Takao :
発見的自己組織化の原理を用いてニューラルネットワーク構造を自己組織化する改良形GMDH-typeニューラルネットワークによる肝臓癌の医用画像診断,
IEICE Technical Report, Vol.PRMU2012-32, 17-22, Sep. 2012.
7. Tadashi Kondo, Junji Ueno and Shoichiro Takao :
予測誤差評価基準にAICを用いる改良形GMDH-typeニューラルネットワークアルゴリズム,
IEICE Technical Report, Vol.KBSE2012-9, 49-54, May 2012.
8. Tadashi Kondo, Junji Ueno and Shoichiro Takao :
多層型人工ニューラルネットワーク構造の自己組織化機能を備えた改良形GMDH-typeニューラルネットワークによる肺癌の医用画像診断,
IEICE Technical Report, Vol.IE2012-1, 1-6, Apr. 2012.
9. Tadashi Kondo, Junji Ueno and Shoichiro Takao :
人工知能技術を用いた多層型GMDH-typeニューラルネットワークによる肝臓癌の医用画像診断,
IEICE Technical Report, Vol.KBSE2011-53, 1-6, Jan. 2012.
10. Tadashi Kondo, Junji Ueno and Shoichiro Takao :
ニューロン構造の自己選択機能を備えたフィードバックGMDH-typeニューラルネットワークによる肺癌の医用画像診断,
IEICE Technical Report, Vol.KBSE2011-54, 7-12, Jan. 2012.
11. Tadashi Kondo :
ネットワーク構造の自己選択を行うフィードバックGMDH-typeニューラルネットワークによる肺癌の医用画像診断,
第34回日本生体医工学会中四国支部講演抄録, 2, Nov. 2011.
12. Tadashi Kondo :
知識ベースを備えた多層型GMDH-typeニューラルネットワークによる肝臓癌の医用画像診断,
第34回日本生体医工学会中四国支部講演抄録, 1, Nov. 2011.
13. Tadashi Kondo :
Medical image diagnosis of lung cancer by revised GMDH-type neural network self-organizing neural network architectuer,
電子情報通信学会技術研究報告, Vol.111, No.121, 7-12, Jul. 2011.
14. Tadashi Kondo :
ネットワーク構造の自己組織化を行う改良形GMDH-typeニューラルネットワークによる肺癌の医用画像診断,
電子情報通信学会技術研究報告, Vol.111, No.121, 1-6, Jul. 2011.
15. Tadashi Kondo :
Development of the medical image diagnosis system using the artificial inlelligence,
Proceedings of Shikoku Branch Conference of Society of Instrument and Control Engineers, No.241, 1-2, Nov. 2010.
16. Tadashi Kondo, Junji Ueno and Shoichiro Takao :
人工知能を用いた肝臓癌の医用画像診断,
Proceedings of JAMIT2010, No.OP4-5, 1-10, Jul. 2010.
17. Tadashi Kondo, Junji Ueno and Shoichiro Takao :
Medical image diagnosis of liver cancer using revised GMDH-type neural network,
電子情報通信学会技術研究報告, Vol.MI2010-42, 27-32, Jul. 2010.
18. Tadashi Kondo and Junji Ueno :
Medical image diagnosis of liver cancer using revised GMDH-type neural network,
第37回知能システムシンポジューム, 135-140, Mar. 2010.
19. Masahiro nakagawa, Tadashi Kondo, Shoichiro Takao and Junji Ueno :
改良形RBFネットワークを用いた肺野領域の画像認識,
中四国放射線医療技術, No.5, 168, Nov. 2009.
20. Tadashi Kondo and Junji Ueno :
Revised GMDH-type neural network self-organizing optimum neural network architecture and its application to 3-dimensional medical image recognition of heart region,
IEICE Technical Report, Vol.MI2009, No.50, 57-62, Jul. 2009.
21. Tadashi Kondo :
Feedback GMDH-type neural network algorithm for medical image analysis and its application to multi-slice CT image analysis of the heart,
IEICE Technical Report, Vol.MBE2009, 1-6, Jul. 2009.
22. Tadashi Kondo :
Three-dimensional medical image recognition of heart region by the feedback GMDH-type neural network self-selecting optimum neural network architecture,
平成21年電気学会電子情報システム部門大会講演論文集, 1245-1250, Mar. 2009.
23. Tadashi Kondo :
ネットワーク構造の自己選択能力を備えた改良形GMDH-typeニューラルネットワークによる医用画像認識,
平成17年度電気関連学会四国支部連合大会講演論文集, 294, Sep. 2005.
24. Tadashi Kondo :
最適なニューラルネットワーク構造の自己選択アルゴリズム,
第15回インテリジェントシステムシンポジューム論文集, 261-266, Sep. 2005.
25. Tadashi Kondo :
最適なニューラルネットワーク構造の自己選択アルゴリズムによる医用画像認識,
電子情報通信学会技術研究報告MBE2005-39-55, Vol.105, No.222, 53-56, Jul. 2005.
26. Tadashi Kondo, Junji Ueno and Kazuya Kondo :
最適なネットワーク構造を自己選択する改良形GMDH-typeニューラルネットワークによる医用画像認識,
第32回知能システムシンポジューム論文集, 33-36, Mar. 2005.
27. Tadashi Kondo :
改良形GMDH-typeニューラルネットワークスによる多層RBFネットワークスの同定,
第48回システム制御情報学会研究発表講演会講演論文集, 435-436, May 2004.
28. Tadashi Kondo :
多層RBFネットワークスを同定する改良形GMDH-typeニューラルネットワークスによる医用画像認識,
システム制御情報学会研究発表講演会論文集, 443-444, May 2004.
29. Tadashi Kondo :
シグモイド関数を用いた改良形GMDH-typeニューラルネットワークスによるX線CT画像のモデリング,
第46回自動制御連合講演会講演論文集, No.TA1-02-2, 17-18, Nov. 2003.
30. Tadashi Kondo :
シグモイド関数を用いた改良形GMDH-typeニューラルネットワークアルゴリズムによる階層型ニューラルネットワークスの構造同定,
第46回自動制御連合講演会講演論文集, No.TA1-02-1, 15-16, Nov. 2003.
31. Tadashi Kondo :
フィードバックループを持つ改良形GMDH-typeニューラルネットワークスによる医用画像認識,
IEICE Technical Report, No.MBE2003-53, 55-58, Jul. 2003.
32. Tadashi Kondo :
ロジスティックGMDH-type ニューラルネットワークスによる医用画像認識,
第47回システム制御情報学会研究発表講演会講演論文集, 639-640, 2003.
33. Tadashi Kondo :
フィードバックループを持つ改良形GMDH-typeニューラルネットワークスによるRBFネットワークスの同定,
第47回システム制御情報学会研究発表講演会講演論文集, 701-702, 2003.
34. Tadashi Kondo :
シグモイド関数を用いたGMDH-typeニューラルネットワークスによる医用画像認識,
第11 回計測自動制御学会中国支部学術講演会論文集, 264-265, Nov. 2002.
35. Tadashi Kondo :
RBFを用いた改良形GMDH-typeニューラルネットワークスによる胃X線画像の認識,
第46回システム制御情報学会研究発表講演会講演論文集, 369-370, May 2002.
36. Tadashi Kondo :
GMDH-typeニューラルネットワークアルゴリズムを用いた階層型ニューラルネットワークスの構造同定,
第46回システム制御情報学会研究発表講演会講演論文集, 537-538, May 2002.
37. Tadashi Kondo :
突然変異と交叉処理を導入したGMDH-typeニューラルネットワークアルゴリズム,
Journal of Shikoku-Section Joint Convention of the Institutes of Electrical and Related Engineers, 286, Sep. 2001.
38. Tadashi Kondo :
ラジアルベース関数を用いる改良形GMDH-typeニューラルネットワークスによる医用画像認識,
IEICE Technical Report, No.MBE2001-52, 57-62, Jul. 2001.
39. Tadashi Kondo :
RBFを用いたGMDH-typeニューラルネットワークスとその医用画像認識への応用,
第45回システム制御情報学会研究発表講演会講演論文集, 537-538, May 2001.
40. Tadashi Kondo :
GAに基づいたGMDH-typeニューラルネットワークアルゴリズム,
第45回システム制御情報学会研究発表講演会講演論文集, 535-536, May 2001.
41. Tadashi Kondo :
フィードバックループを持つGMDH-typeニューラルネットワークスによる大気汚染濃度パターンの同定,
第45回システム制御情報学会研究発表講演会講演論文集, 539-540, May 2001.
42. Tadashi Kondo :
GMDH-typeニューラルネットワークスとその医用画像認識への応用,
第43回自動制御連合講演会前刷, 185-186, Nov. 2000.
43. Tadashi Kondo :
ロジスティックGMDH-typeニューラルネットワークス,
第43回自動制御連合講演会前刷, 189-190, Nov. 2000.
44. Tadashi Kondo :
フィードバックループを持つGMDH-typeニューラルネットワークス,
第43回自動制御連合講演会前刷, 187-188, Nov. 2000.
45. Tadashi Kondo :
ラジアルベース関数を用いるGMDH-typeニューラルネットワークスとその医用画像認識への応用,
第23回日本ME学会中国四国支部大会論文集, 20, Oct. 2000.
46. Tadashi Kondo :
GMDHニューラルネットワークの学習アルゴリズムとその肺野領域自動抽出問題への応用,
第42回システム制御情報学会研究発表講演会講演論文集, 389-390, 1998.
47. Tadashi Kondo :
GMDH法によるX線CT画像を対象にした肝臓の画像認識,
第41回システム制御情報学会研究発表講演会講演論文集, 469-470, 1997.
48. Tadashi Kondo :
GMDH法を用いたニューラルネットワークの構造同定アルゴリズム,
第41回システム制御情報学会研究発表講演会講演論文集, 491-492, 1997.
49. Tadashi Kondo :
GMDHニューラルネットワークアルゴリズムとその医用画像認識への応用,
計測自動制御学会第36回学術講演会予稿集, 735-736, 1997.
50. Tadashi Kondo :
発見的自己組織化の原理を用いたGMDHニーラルネットワークの学習アルゴリズム,
Journal of Shikoku-Section Joint Convention of the Institutes of Electrical and Related Engineers, 248, 1997.
51. Tadashi Kondo :
ニューロン構造の自己選択能力を備えたGMDHニューラルネットワークアルゴリズム,
第40回自動制御連合講演会前刷, 425-426, 1997.
52. Tadashi Kondo :
特徴量の自己選択能力を備えた医用画像認識用ニューラルネットワーク,
第40回システム制御情報学会研究発表講演会講演論文集, 31-32, 1996.
53. Tadashi Kondo :
特徴量の自己発生能力を備えたGMDHtypeニューラルネットワークによる医用画像認識,
計測自動制御学会第35回学術講演会予稿集, 267-268, 1996.
54. Tadashi Kondo :
GMDH typeニューラルネットワークアルゴリズム,
第39回システム制御情報学会研究発表講演会講演論文集, 111-112, 1995.
55. Tadashi Kondo :
入力変数の自己選択能力を備えたニューラルネットワーク,
Journal of Shikoku-Section Joint Convention of the Institutes of Electrical and Related Engineers, 296, 1995.
56. Tadashi Kondo :
複雑な構造をした非線形システムの同定を目的としたニューラルネットワークにおける構造同定アルゴリズム,
第38回システム制御情報学会研究発表講演会講演論文集, 135-136, 1994.

Report:

1. Tadashi Kondo :
GMDH-typeニューラルネットワークスによるコンピュータ支援画像診断システム,
平成14年度ー平成15年度科学研究費補助金(基盤研究(C)(2))研究成果報告書, May 2004.
2. Tadashi Kondo :
フィードバックループを持つ改良形GMDH-typeニューラルネットワークスによる医用画像認識,
IEICE Technical Report, 2003.
3. Tadashi Kondo :
ラジアルベース関数を用いる改良形GMDH-typeニューラルネットワークスによる医用画像認識,
IEICE Technical Report, 2001.
4. Tadashi Kondo :
医用画像認識を目的とした神経回路網モデルの基礎的研究,
平成七年度徳島大学教育研究学内特別経費による報告書, 542-547, 1997.
5. Tadashi Kondo :
実システムへの応用を目的とした大規模神経回路網モデルの自己形成に関する研究,
平成六年度徳島大学教育研究学内特別経費による研究報告書, 688-696, 1996.
6. Tadashi Kondo :
神経回路網モデルとGMDH法による実システムのモデリング,
平成五年度徳島大学教育研究学内特別経費による研究報告書, 768-777, 1995.
7. Tadashi Kondo :
神経回路網モデルと改良形GMDH法(発見的自己組織化法)に関する基礎的研究,
平成四年度徳島大学教育研究学内特別経費による研究報告書, 771-780, 1994.
8. Tadashi Kondo :
神経回路網モデルを用いた非線形パターンの同定,
平成元年度徳島大学教育研究学内特別経費による研究報告書, 469-478, 1991.

Grants-in-Aid for Scientific Research (KAKEN Grants Database @ NII.ac.jp)

  • 深層学習とディープGMDH型人工知能技術による医用画像診断と感性工学への応用 (Project/Area Number: 18K04206 )
  • Medical image analysis of abdominal X-ray CT images by hybrid deep neural network of deep logistic GMDH-type neural network and convolutional neural network (Project/Area Number: 15K06145 )
  • Three dimensional medical image diagnosis of lung, liver and brain using new artificial neural network (Project/Area Number: 26420421 )
  • Abdominal CT image analysis and computa assisted diagnonsis with new artificial intelligence (Project/Area Number: 24560497 )
  • Development of 3 dimensional medical image diagnosis system using artificial intelligence (Project/Area Number: 22560403 )
  • Developments of Computer Aided Diagnosis System of liver cancers using knowledge Engineering for Medical X-ray CT Images (Project/Area Number: 21560428 )
  • Three-dimensional medical image analysis of the organ regions using artificial neural networks (Project/Area Number: 19500389 )
  • Medical image recognition of lungs regions for multi-slice CT images by using the revised GMDH-type neural networks. (Project/Area Number: 15560349 )
  • COMPUTER AIDED DIAGNOSIS USING GMDH-TYPE NEURAL NETWORKS (Project/Area Number: 14550401 )
  • Search by Researcher Number (80205559)