Profile
- Bachelor of Engineering from Tokushima University Master of Engineering and Doctor of Engineering from Osaka University
- Former Head of Control Research, Heavy Apparatus Engineering Laboratory, Toshiba Corporation Former Professor, Tokushima University Faculty of Medicine Former Professor, Graduate School of Health Sciences Former Professor, Graduate School of Biomedical Sciences
- Professor Emeritus, Tokushima University
Message
My field of specialization is medical informatics. Recently, artificial intelligence (AI) and data science have become a worldwide boom, and we often see the words AI and data science on TV and in newspapers.AI and data science are also being applied to the medical field, and are now being put to practical use in disease diagnosis and image diagnosis.
In this lecture, we will study image diagnosis using AI. Artificial intelligence has experienced two global booms in the past.The first was in the 1960s, when computers were not yet powerful enough and problems with mathematical theories of artificial intelligence were pointed out, and the boom rapidly died out. The second boom was in the 1980s, when expert systems and neural networks (neural network models) using the error back propagation method (BP method) attracted attention, but these artificial intelligence technologies also had problems with practical applications, and the boom died out.
This is the third AI boom, and this time the artificial intelligence technology called deep learning has attracted attention and has been applied to actual problems with remarkable results. Globally, the United States and China are leading the world in the development of AI technology and its application to real systems. Unfortunately, Japan is lagging far behind in AI research and technology development. In order to make up for this lag, I think it is important for young students studying at universities and graduate schools to fully master the fundamental technologies of AI and data science, and to acquire the skills to apply them to real systems.
The Kyoto College of Graduate Studies for Informatics is the most suitable educational institution to acquire advanced technologies at the graduate level, such as AI, data science, and IT technologies. I hope that all of you will study and master advanced technologies such as AI, data science, and IT technologies, and play an active role in society.
Responsible Subject
- Medical Frontier Informatics
Field of Specialization
- Medical informatics
- Artificial intelligence engineering
- Data Science
- Medical image processing
Business Performance
Academic papers, papers presented at international conferences, etc.
- 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.
- 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
- 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.
- 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.
- 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.
- 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.
- 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.
- 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.
- 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.
- 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.
and about 200 others.