| Project/Area Number |
60440043
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| Research Category |
Grant-in-Aid for General Scientific Research (A)
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| Allocation Type | Single-year Grants |
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| Research Field |
内科学一般
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| Research Institution | University of Tokyo |
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Principal Investigator |
FURUKAWA Toshiyuki Faculty of Medicine, University of Tokyo, Professor, 医学部, 教授 (20101082)
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| Co-Investigator(Kenkyū-buntansha) |
KAIHARA Shigekoto Faculty of Medicine, University of Tokyo, Professor, 医学部, 教授 (30010234)
SUGIMOTO Tuneaki Faculty of Medicine, University of Tokyo, Professor, 医学部, 教授 (60019883)
田中 博 東京大学, 医学部, 講師 (60155158)
尾上 守夫 東京大学, 生産技術研究所, 教授 (70013076)
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| Project Period (FY) |
1985 – 1988
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| Project Status |
Completed (Fiscal Year 1988)
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| Budget Amount *help |
¥29,500,000 (Direct Cost: ¥29,500,000)
Fiscal Year 1988: ¥2,500,000 (Direct Cost: ¥2,500,000)
Fiscal Year 1987: ¥1,700,000 (Direct Cost: ¥1,700,000)
Fiscal Year 1986: ¥2,300,000 (Direct Cost: ¥2,300,000)
Fiscal Year 1985: ¥23,000,000 (Direct Cost: ¥23,000,000)
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| Keywords | New generation computer / New generation computer-aided diagnosis / hierarchical inference logic / Artificial intelligence / Knowledge formation / Ambiguity of biological data / Disease process model / Inverse solution / 不完全データ / 並列処理方式 / コンピュータ診断機構 / データ通信 / 知識自己拡張 / 自動学習機能 / エキスパートシステム / 病態生理学的ネットワークモデル / 疾病経過のゆらぎ概念 / ロジスティック関数 / 指数ワイブル関数 / マルコフ型時間系列モデル / 病態観測密度の最適化 / 認識スキーマのゆらぎ / 多変量解析モデル / 逆問題モデル / 知識工学モデル / 新しい推論エンジン / 階層的メタ・ルール / 人工知能型推論 |
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| Research Abstract |
In order to develope the new software algorithms for the new generation computeraided diagnosis, a series of study for 4 years was completed.
(1) Hierarchical tree structure logics for the clinical decision making were studied using the real cases of infusion therapy. It showed the decision capability fairly resembled to that of physicians.
(2) Multivariate statistical techniques using the incomplete data cources were studied. The study revealed the efficacy of the maximum entropy method to substitute the lack of necessary data.
(3) The clinical courses of disease were simulated by a network with nodes correspond to the states of the disease. These models showed good agreement with the data of clinical epidemiological studies. There should be a certain minimum spacial and time distance of clinical examinations in order to describe the clinical course of the diseases. The proposal is the application of multivariate statistical technique to determing the spacial distance, and the Markov process model to determine the time distance of the examination.
(4) A parallel data processing using a number of microcomputers was introduced in the case of an expert system to the infusion therapy, and the communication and data exchange between the different computers with different operation systems and/or different computer languages could be effectively coordinated. In the study, the simulation model of body fluid regulation physiology was implemented in a computer, and the decision logic of an artificial intelligence was equipped into another computer. In addition, the process of learning of physician was analyzed by a multivariate statistical model, and the community between them was found. It is fundamental condition to give an appropriate data base (teaching) at very early stage of learning is the most important factor in not only the maturation of physician's knowledge but that of computer-aided diagnostic logics.
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