Tadashi Kondo

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Revised RBF network algorithm and its application to the interactive art system

Chihiro Kondo, Tadashi Kondo, 2009, 2009 ICCAS-SICE.

Medical Image Analysis of Brain X-ray CT Images By Deep GMDH-Type Neural Network

Tadashi Kondo, Junji Ueno, Shoichiro Takao, 2016, J. Robotics Netw. Artif. Life.

Medical Image Recognition by using Revised GMDH-type Neural Networks with a Feedback loop

Tadashi Kondo, 2003 .

Recognition of 3-dimensional medical images of the lungs, pulmonary vessels and bronchial trees by artificial neural networks

Masahiro Nakagawa, Tadashi Kondo, Takaomi Matuki, 2008 .

Learning algorithm of the revised RBF network and its application to the media art system

Chihiro Kondo, Tadashi Kondo, 2010, Artificial Life and Robotics.

Revised GMDH-type neural network using artificial intelligence and its application to medical image diagnosis

Tadashi Kondo, T. Kondo, 2011, 2011 IEEE Workshop On Hybrid Intelligent Models And Applications.

Medical image diagnosis of lung cancer by a revised GMDH-type neural network using various kinds of neuron

Tadashi Kondo, Junji Ueno, 2011, Artificial Life and Robotics.

Medical Image Recognition of Heart Regions by Deep Multi-Layered GMDH-Type Neural Network Using Principal Component-Regression Analysis

Tadashi Kondo, Junji Ueno, Shoichiro Takao, 2015, J. Robotics Netw. Artif. Life.

GMDH-type neural networks and their application to the medical image recognition of the lungs

Jacek M. Zurada, Tadashi Kondo, A. S. Pandya, 1999, SICE '99. Proceedings of the 38th SICE Annual Conference. International Session Papers (IEEE Cat. No.99TH8456).

Revised GMDH-type neural network algorithm with a feedback loop identifying sigmoid function neural network

Tadashi Kondo, Junji Ueno, 2006 .

Identification of Furnace Heat Patterns by a Neural Network Identifying Nonlinear Complex System

Tadashi Kondo, 1993 .

Deep Feedback GMDH-Type Neural Network Using Principal Component-Regression Analysis and Its Application to Medical Image Recognition of Abdominal Multi-Organs

Tadashi Kondo, Junji Ueno, Shoichiro Takao, 2015, J. Robotics Netw. Artif. Life.

Deep feedback GMDH-type neural network and its application to medical image analysis of MRI brain images

Tadashi Kondo, Junji Ueno, Shoichiro Takao, 2017, Artificial Life and Robotics.

Revised GMDH-Type Neural Networks Using AIC or PSS Criterion and Their Application to Medical Image Recognition

Tadashi Kondo, Junji Ueno, Kazuya Kondo, 2005, J. Adv. Comput. Intell. Intell. Informatics.

Identification of the Multi-layered Neural Networks by Revised GMDH-Type Neural Network Algorithm with PSS Criterion

Abhijit S. Pandya, Tadashi Kondo, 2004, KES.

Medical image recognition by using logistic GMDH-type neural networks

Abhijit S. Pandya, Tadashi Kondo, 2001, SICE 2001. Proceedings of the 40th SICE Annual Conference. International Session Papers (IEEE Cat. No.01TH8603).

Medical image analysis of abdominal X-ray CT images by deep multi-layered GMDH-type neural network

Tadashi Kondo, Junji Ueno, Shoichiro Takao, 2017, Artificial Life and Robotics.

Three-dimensional medical image analysis of the heart by the revised GMDH-type neural network self-selecting optimum neural network architecture

Chihiro Kondo, Tadashi Kondo, Junji Ueno, 2009, Artificial Life and Robotics.

Hybrid Multi-layered GMDH-Type Neural Network Using Principal Component-Regression Analysis and Its Application to Medical Image Diagnosis of Lung Cancer

Tadashi Kondo, Junji Ueno, Shoichiro Takao, 2012, 2012 ASE/IEEE International Conference on BioMedical Computing (BioMedCom).

Hybrid feedback GMDH-type neural network self-selecting various neurons and its application to medical image diagnosis of lung cancer

Tadashi Kondo, Junji Ueno, Shoichiro Takao, 2012, The 6th International Conference on Soft Computing and Intelligent Systems, and The 13th International Symposium on Advanced Intelligence Systems.

Medical image recognition of cancer of the liver by GMDH-type neural network

Masahiro Nakagawa, Tadashi Kondo, Junji Ueno, 2010 .

Logistic GMDH-type neural networks and their application to the identification of the X-ray film characteristic curve

Jacek M. Zurada, Tadashi Kondo, A. S. Pandya, 1999, IEEE SMC'99 Conference Proceedings. 1999 IEEE International Conference on Systems, Man, and Cybernetics (Cat. No.99CH37028).

The learning algorithms of the GMDH neural network and their application to the medical image recognition

Tadashi Kondo, 1998, Proceedings of the 37th SICE Annual Conference. International Session Papers.

Medical Image Analysis of MRI Brain Images by Deep RBF GMDH-type Neural Network Using Principal Component-Regression Analysis

Tadashi Kondo, Junji Ueno, Shoichiro Takao, 2015, 2015 IIAI 4th International Congress on Advanced Applied Informatics.

Development of the Starling Engine Adapted to a Small Passenger Car

Tadashi Kondo, Hiroyuki Ouchi, Masahiko Hasegawa, 1987 .

Medical Image Diagnosis of Liver Cancer by Multi-layered GMDH-type Neural Network Using Artificial Intelligence Technology

Tadashi Kondo, Junji Ueno, Shoichiro Takao, 2012 .

GMDH-type neural network algorithm with a feedback loop for structural identification of RBF neural network

Abhijit S. Pandya, Hirofumi Nagashino, Tadashi Kondo, 2007, Int. J. Knowl. Based Intell. Eng. Syst..

Medical Image Diagnosis of Liver Cancer by Multi-layered GMDH-type Neural Network Using Principal Component-Regression Analysis and PSS Criterion

Tadashi Kondo, Junji Ueno, Shoichiro Takao, 2013 .

Modeling of X-ray CT image by using revised GMDH-type neural networks with sigmoid functions

Abhijit S. Pandya, Tadashi Kondo, 2003, Proceedings 2003 IEEE International Symposium on Computational Intelligence in Robotics and Automation. Computational Intelligence in Robotics and Automation for the New Millennium (Cat. No.03EX694).

Revised GMDH-type neural network using principal component-regression analysis

Tadashi Kondo, Junji Ueno, 2011, SICE Annual Conference 2011.

Structural identification of the multi-layered neural networks by using revised GMDH-type neural network algorithm with a feedback loop

Abhijit S. Pandya, Tadashi Kondo, 2003, SICE 2003 Annual Conference (IEEE Cat. No.03TH8734).

Medical Image Diagnosis of Liver Cancer by Hybrid Feedback GMDH-type Neural Network using Heuristic Self-Organization

Tadashi Kondo, Junji Ueno, Schoichiro Takao, 2012 .

Feedback GMDH-Type Neural Network Algorithm Using Prediction Error Criterion Defined as AIC

Tadashi Kondo, Junji Ueno, Shoichiro Takao, 2012 .

Revised GMDH Algorithm Estimating Degree of the Complete Polynomial

Tadashi Kondo, Tadashi Kondo, T. Kondo, 1986 .

Feedback GMDH-type neural network algorithm and its application to medical image analysis of cancer of the liver

Chihiro Kondo, Tadashi Kondo, Junji Ueno, 2010, Artificial Life and Robotics.

GMDH neural network algorithm using the heuristic self-organization method and its application to the pattern identification problem

Tadashi Kondo, T. Kondo, 1998, Proceedings of the 37th SICE Annual Conference. International Session Papers.

Feedback GMDH-type Neural Network Self-Selecting Various Functions and Its Application to Medical Image Diagnosis of Lung Cancer

Tadashi Kondo, Junji Ueno, Shoichiro Takao, 2012, 2012 13th ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing.

Three-Dimensional Medical Image Recognition of Blood Vessels by Multi-Layered GMDH-Type Neural Network Self-Selecting Optimum Neural Network Architecture

Tadashi Kondo, 2007 .

Feedback RBF GMDH-Type Neural Network Using Principal Component-Regression Analysis and Its Application to Medical Image Diagnosis of Lung Cancer

Tadashi Kondo, Junji Ueno, Shoichiro Takao, 2013, 2013 First International Symposium on Computing and Networking.

Multi-layered GMDH-type Neural Network Algorithm Using Principal Component-Regression Analysis and PSS Criterion

Tadashi Kondo, Junji Ueno, Shoichiro Takao, 2013 .

Medical Image Diagnosis of Liver Cancer Using a Neural Network and Artificial Intelligence

Tadashi Kondo, Junji Ueno, Shoichiro Takao, 2011, J. Adv. Comput. Intell. Intell. Informatics.

Recognition of X-ray Images by Using Revised GMDH-type Neural Networks

Abhijit S. Pandya, Tadashi Kondo, 2003, KES.

GMDH-type neural networks: with radial basis functions and their application to medical image recognition of the brain

Tadashi Kondo, A. S. Pandya, 2000, SICE 2000. Proceedings of the 39th SICE Annual Conference. International Session Papers (IEEE Cat. No.00TH8545).

Medical Image Diagnosis of Liver Cancer by Revised GMDH-type Neural Network Using Feedback Loop Calculation

Tadashi Kondo, Junji Ueno, Shoichiro Takao, 2012, 2012 Sixth International Conference on Genetic and Evolutionary Computing.

Accelerated organ region segmentation by the revised radial basis function network using a graphics processing unit.

Takeshi Konishi, Tadashi Kondo, Jun Hirose, 2019, The journal of medical investigation : JMI.

Medical image diagnosis of kidney regions by deep feedback GMDH-type neural network using principal component-regression analysis

Tadashi Kondo, Junji Ueno, Shoichiro Takao, 2016, Artificial Life and Robotics.

Hybrid multi-layered GMDH-type neural network self-selecting various neurons and its application to medical image diagnosis of liver cancer

Tadashi Kondo, Junji Ueno, Shoichiro Takao, 2012, The 6th International Conference on Soft Computing and Intelligent Systems, and The 13th International Symposium on Advanced Intelligence Systems.

Revised GMDH-type neural networks with radial basis functions and their application to medical image recognition of stomach

Tadashi Kondo, 2003 .

Hybrid GMDH-type neural network using artificial intelligence and its application to medical image diagnosis of liver cancer

Tadashi Kondo, Junji Ueno, Shoichiro Takao, 2011, 2011 IEEE/SICE International Symposium on System Integration (SII).

Logistic GMDH-type neural network using principal component-regression analysis and its application to medical image diagnosis of lung cancer

Tadashi Kondo, Junji Ueno, Shoichiro Takao, 2015, Artificial Life and Robotics.

Detection algorithm for conceptual difference among different persons-as an example of emergence in the human interaction

Tadashi Kondo, N. Saiwaki, S. Nishida, 1997, 1997 IEEE International Conference on Systems, Man, and Cybernetics. Computational Cybernetics and Simulation.

Nonlinear Pattern Identification by Multi-layered GMDH-Type Neural Network Self-selecting Optimum Neural Network Architecture

Tadashi Kondo, 2007, ICONIP.

TECHNICAL SOLUTION IN A CENTRAL STATION RE-DEVELOPMENT UNDER RAILWAY OPERATION RESTRICTED BY VARIOUS URBAN CONDITIONS

Yasuhiro Yamada, Tadashi Kondo, Ikuo Tanaka, 2011 .

Prediction of stock market characteristics using neural networks

Abhijit S. Pandya, Tadashi Kondo, Trupti U. Shah, 1999, Defense, Security, and Sensing.

Medical image recognition of the Lungs by using the neural netaork

Tadashi Kondo, 1997 .

Three-dimensional medical image recognition of the heart by revised GMDH-type neural network algorithm

Chihiro Kondo, Tadashi Kondo, 2009, 2009 ICCAS-SICE.

Medical image diagnosis of lung cancer by revised GMDH-type neural network self-selecting optimum neuron architectures

Tadashi Kondo, Junji Ueno, Shoichiro Takao, 2011, 2011 IEEE/SICE International Symposium on System Integration (SII).

Hybrid feedback GMDH-type neural network using principal component-regression analysis and its application to medical image recognition of heart regions

Tadashi Kondo, Junji Ueno, Shoichiro Takao, 2014, 2014 Joint 7th International Conference on Soft Computing and Intelligent Systems (SCIS) and 15th International Symposium on Advanced Intelligent Systems (ISIS).

Logistic GMDH-Type Neural Network and its Application to Identification of X-Ray Film Characteristic Curve

Tadashi Kondo, Junji Ueno, 2007, J. Adv. Comput. Intell. Intell. Informatics.

Medical Image Recognition of Abdominal Multi-organs by Hybrid Multi-layered GMDH-type Neural Network Using Principal Component-Regression Analysis

Tadashi Kondo, Junji Ueno, Shoichiro Takao, 2014, 2014 Second International Symposium on Computing and Networking.

MEDICAL IMAGE RECOGNITION OF ABDOMINAL MULTI-ORGANS BY RBF GMDH-TYPE NEURAL NETWORK

Tadashi Kondo, Junji Ueno, 2009 .

Revised GMDH-type neural networks with a feedback loop and their application to the medical image recognition

Abhijit S. Pandya, Tadashi Kondo, 2002, Proceedings of the 9th International Conference on Neural Information Processing, 2002. ICONIP '02..

Medical image diagnosis of liver cancer by hybrid feedback GMDH-type neural network using principal component-regression analysis

Tadashi Kondo, Junji Ueno, Shoichiro Takao, 2015, Artificial Life and Robotics.

Recognition of 3-dimensional medical images of the head by radial basis function (RBF) neural network

Masahiro Nakagawa, Tadashi Kondo, Takaomi Matuki, 2008 .

FEEDBACK GMDH-TYPE NEURAL NETWORK AND ITS APPLICATION TO MEDICAL IMAGE ANALYSIS OF LIVER CANCER

Tadashi Kondo, Junji Ueno, T. Kondo, 2011 .

Multiinput-Multioutput Type GMDH Algorithm Using Regression-Principal Component Analysis

Tadashi Kondo, 1993 .

Multilayered GMDH-Type Neural Network with Radial Basis Functions and its Application to 3-Dimensional Medical Image Recognition of the Liver

Abhijit S. Pandya, Tadashi Kondo, Junji Ueno, 2007, J. Adv. Comput. Intell. Intell. Informatics.

GMDH Type Neural Network Algorithm Identifying a Network Structure with the Heuristic Self-Organization Method

Tadashi Kondo, 1998 .

Medical image recognition of the white and gray matters of the brain by radial basis function (RBF) neural network

Masahiro Nakagawa, Tadashi Kondo, Junji Ueno, 2009 .

Medical Image Recognition by Revised GMDH-type Neural Network Algorithm with a Feedback Loop Identifying Sigmoid Function Neural Network

Tadashi Kondo, 2006 .

Identification of the interactive art system using the revised RBF network

Chihiro Kondo, Tadashi Kondo, 2010 .

Neural Network with a Self-Selection Ability of Network Structure and Its Application to Nonlinear System Identification

Tadashi Kondo, 1995 .

Medical image diagnosis of liver cancer by feedback GMDH-type neural network using knowledge base

Tadashi Kondo, Junji Ueno, Shoichiro Takao, 2012, Artificial Life and Robotics.

Medical image diagnosis of lung cancer by feedback gmdh-type neural network self-selecting neural network architecture

Tadashi Kondo, Junji Ueno, Shoichiro Takao, 2012 .

Nonlinear system identification by feedback GMDH-type neural network with architecture self-selecting function

Tadashi Kondo, Junji Ueno, 2010, 2010 IEEE International Symposium on Intelligent Control.

In Search of Universal Haiku Grammar : Introduction

Tadashi Kondo, 1990 .

Multi-layered GMDH-type neural network self-selecting optimum neural network architecture and its application to 3-dimensional medical image recognition of blood vessels

Tadashi Kondo, Junji Ueno, 2008 .

Identification of radial basis function networks by using revised GMDH-type neural networks with a feedback loop

Tadashi Kondo, 2002, Proceedings of the 41st SICE Annual Conference. SICE 2002..

Three-dimensional medical image recognition of cancer of the liver by a revised radial basis function (RBF) neural network algorithm

Masahiro Nakagawa, Tadashi Kondo, Junji Ueno, 2009, Artificial Life and Robotics.

Foreign currency rate forecasting using neural networks

Abhijit S. Pandya, Tadashi Kondo, Suryaprasad Jayadevappa, 2000, SPIE Defense + Commercial Sensing.

Neural Network Identifying Nonlinear Complex System

Tadashi Kondo, 1991 .

Toyota “ECT-i” a New Automatic Transmission with Intelligent Electronic Control System

Tadashi Kondo, Kunihiro Iwatsuki, Yutaka Taga, 1990 .

Planter with a platform for operation

Tadashi Kondo, Toshiro Wada, Yuji Ohara, 1994 .

Deep multi-layered GMDH-type neural network using revised heuristic self-organization and its application to medical image diagnosis of liver cancer

Tadashi Kondo, Junji Ueno, Shoichiro Takao, 2017, Artificial Life and Robotics.

Link and Shift--A Practical Guide to Renku Composition

Tadashi Kondo, William J. Higginson, 1994 .

Medical image recognition of the brain by revised GMDH-type neural network algorithm with a feedback loop

Tadashi Kondo, Junji Ueno, 2006 .

Medical Image Diagnosis of Liver Cancer Using Multi-layered GMDH-type Neural Network

Tadashi Kondo, Junji Ueno, 2010, SOCO 2010.

Hybrid Multi-layered GMDH-Type Neural Network Using Principal Component-Regression Analysis and Its Application to Medical Image Diagnosis of Lung Cancer

Tadashi Kondo, Junji Ueno, Schoichiro Takao, 2012 .

The 3-dimensional medical image recognition of right and left kidneys by deep GMDH-type neural network

Tadashi Kondo, Junji Ueno, Shoichiro Takao, 2015, 2015 International Conference on Intelligent Informatics and Biomedical Sciences (ICIIBMS).

Medical image recognition of MRI brain images using deep logistic GMDH-type neural network and convolutional neural network

Tadashi Kondo, 2019 .

Revised GMDH Algorithm Using Quantified Input Variables with the Application to Rolling Model Identification

Tadashi Kondo, Yoshiharu Anbe, Hisashi Ezure, 1984 .

Revised GMDH-type neural network algorithm for medical image recognition and its application to 3-dimensional medical image analysis of the heart

Tadashi Kondo, Junji Ueno, 2009 .

Large-Spatial Pattern Identification of Air Pollution by a Combined Model of Source-Receptor Matrix and Revised GMDH

Tadashi Kondo, Hiroyuki Tamura, 1977 .

Neural Network with a Self-Selection Ability of Input Variables for a Nonlinear System Identification

Tadashi Kondo, 1997 .

Nonlinear Steady State Modeling for River Quality by a Neural Network with a Self-Selection Ability of Network Structure

Tadashi Kondo, 1997 .

Medical Image Diagnosis of Lung Cancer by Deep Feedback GMDH-Type Neural Network

Tadashi Kondo, Junji Ueno, Shoichiro Takao, 2016, J. Robotics Netw. Artif. Life.

Revised GMDH Algorithm Identifying Nonlinear Exponential Type Model

Tadashi Kondo, 1986 .

Medical Image Recognition of Abdominal Organs by RBF GMDH-type Neural Network

Tadashi Kondo, Junji Ueno, 2008 .

Revised GMDH-type neural network algorithm self-selecting optimum neural network architecture

Chihiro Kondo, Tadashi Kondo, 2009, Artificial Life and Robotics.

A New Multi-layered GMDH-type Neural Network Algorithm Using Principal Component-Regression Analysis

Tadashi Kondo, Junji Ueno, Shoichiro Takao, 2012 .

Medical image analysis of chest images using deep multi-layered GMDH-type neural network and convolutional neural network

Tadashi Kondo, 2020 .

Medical image diagnosis of liver cancer using deep RBF GMDH-type neural network

Tadashi Kondo, 2018 .

Three-dimensional medical image recognition of the lung by the revised radial basis function (RBF) network algorithm

Masahiro Nakagawa, Tadashi Kondo, 2010 .

Medical image diagnosis of lung cancer by revised GMDH-type neural network using heuristic self-organization

Tadashi Kondo, Junji Ueno, 2011, SICE Annual Conference 2011.

Three-dimensional medical image recognition of the cancer of the liver by artificial neural network

Masahiro Nakagawa, Tadashi Kondo, Junji Ueno, 2009 .

Medical image diagnosis of lung cancer by multi-layered GMDH-type neural network self-selecting functions

Tadashi Kondo, Junji Ueno, Shoichiro Takao, 2013, Artificial Life and Robotics.

The Proteomic Profile of Pancreatic Cancer Cell Lines Corresponding to Carcinogenesis and Metastasis

Tadashi Kondo, Kiyonaga Fujii, Setsuo Hirohashi, 2009 .

Preoperative 3D volumetric analysis for liver congestion applied in a patient with hilar cholangiocarcinoma

Tadashi Kondo, Ryoko Sasaki, Nobuhiro Ohkohchi, 2010, Langenbeck's Archives of Surgery.

Isolated spleen recurrence in a patient with lung adenocarcinoma: A case report.

Tadashi Kondo, H. Satoh, T. Kondo, 2015, Experimental and therapeutic medicine.

Tissue proteomics for cancer biomarker development: laser microdissection and 2D-DIGE.

Tadashi Kondo, T. Kondo, 2008, BMB reports.

Cancer biomarker development and two-dimensional difference gel electrophoresis (2D-DIGE).

Tadashi Kondo, T. Kondo, 2019, Biochimica et biophysica acta. Proteins and proteomics.

Developments for a growing Japanese patient population: facilitating new technologies for future health care.

Fumio Nomura, Tadashi Kondo, Toshihide Nishimura, 2011, Journal of proteomics.

Secernin-1 as a novel prognostic biomarker candidate of synovial sarcoma revealed by proteomics.

Akihiko Yoshida, Kazutaka Kikuta, Tadashi Kondo, 2011, Journal of proteomics.

Proteomic signature of human cancer cells

Tadashi Kondo, Shoji Kudoh, Setsuo Hirohashi, 2004, Proteomics.

Global Protein-expression Analysis of Bone and Soft Tissue Sarcomas

Kazutaka Kikuta, Tadashi Kondo, Akira Kawai, 2008, Clinical orthopaedics and related research.

Alternative splice variant of actinin-4 in small cell lung cancer

Tadashi Kondo, Setsuo Hirohashi, Tesshi Yamada, 2004, Oncogene.

Prognostic significance of promyelocytic leukemia expression in gastrointestinal stromal tumor; integrated proteomic and transcriptomic analysis

Akihiko Yoshida, Tadashi Kondo, Tatsuo Kanda, 2014, Cancer science.

Antibody-based Protein Profiling of the Human Chromosome 21

Emma Lundberg, Tadashi Kondo, Åsa Sivertsson, 2011, Molecular & Cellular Proteomics.

Morphological and transcriptional responses of untransformed intestinal epithelial cells to an oncogenic β-catenin protein

Tadashi Kondo, Setsuo Hirohashi, Kohzoh Imai, 2005, Oncogene.

Proteomic signatures for histological types of lung cancer

Tadashi Kondo, Shoji Kudoh, Setsuo Hirohashi, 2005, Proteomics.

Application of sensitive fluorescent dyes in linkage of laser microdissection and two‐dimensional gel electrophoresis as a cancer proteomic study tool

Tadashi Kondo, Setsuo Hirohashi, Tesshi Yamada, 2003, Proteomics.

Proteomic Signature Corresponding to the Response to Gefitinib (Iressa, ZD1839), an Epidermal Growth Factor Receptor Tyrosine Kinase Inhibitor in Lung Adenocarcinoma

Tadashi Kondo, Toshihide Nishimura, Kiyonaga Fujii, 2007, Clinical Cancer Research.