| Project/Area Number |
16200039
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| Research Category |
Grant-in-Aid for Scientific Research (A)
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| Allocation Type | Single-year Grants |
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| Section | 一般 |
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| Research Field |
Medical systems
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| Research Institution | The University of Tokyo |
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Principal Investigator |
OHE Kazuhiko The University of Tokyo, THE UNIVERSITY OF TOKYO HOSPITAL, PROFESSOR (40221121)
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| Co-Investigator(Kenkyū-buntansha) |
ONOGI Yuzo INTERNATIONAL UNIVERSITY OF HEALTH AND WELFARE, MITA HOSPITAL, Assoc. PROFESSOR (90233593)
HATANO Kenji THE UNIVERSITY OF TOKYO, Graduate School of Medicine, RESEARCH Assoc (60311619)
MIYOK Kengo THE UNIVERSITY OF TOKYO HOSPITAL, 医学部附属病院, LECTURER (40302690)
SHINOHARA Nobuo THE UNIVERSITY OF TOKYO HOSPITAL, 医学部附属病院, RESEARCH Assoc (90345223)
YAMAGUCHI Izumi THE UNIVERSITY OF TOKYO HOSPITAL, 医学部附属病院, RESEARCH Assoc (80345222)
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| Project Period (FY) |
2004 – 2007
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| Project Status |
Completed (Fiscal Year 2007)
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| Budget Amount *help |
¥46,540,000 (Direct Cost: ¥35,800,000、Indirect Cost: ¥10,740,000)
Fiscal Year 2007: ¥13,260,000 (Direct Cost: ¥10,200,000、Indirect Cost: ¥3,060,000)
Fiscal Year 2006: ¥14,300,000 (Direct Cost: ¥11,000,000、Indirect Cost: ¥3,300,000)
Fiscal Year 2005: ¥8,580,000 (Direct Cost: ¥6,600,000、Indirect Cost: ¥1,980,000)
Fiscal Year 2004: ¥10,400,000 (Direct Cost: ¥8,000,000、Indirect Cost: ¥2,400,000)
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| Keywords | ONTOLOOGY / THESAURUS / NATURAL LANGUAGE PROCESSING / ELECTRONIC MEDICAL RECORD / HEALTH INFORMATION SYSTEMS / MEDICAL TERMINOLOGY / KNOWLEDGE-BASED SYSTEMS / 医療用語 |
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| Research Abstract |
For the purpose of developing large-scale medical ontology for clinical use, we conducted the following four subjects in the research period.
1) Automatic extraction and classification of relationship among clinical terminology from medical dictionary
2) Automatic extraction of relationship among human body elements
3) Automatic extraction of important clinical findings from diagnostic reports
4) Consideration about database structure for large-scale medical ontology
After the above work, we developed a top-level ontology framework, using ontology editor "HOZO", in the domain of internal medicine, surgery, clinical findings, surgical procedure, and anatomy. For example, general disease concept was classified into formal disease that can be represented by the etiology of the disease, syndrome that can be represented only by the list of clinical findings and symptoms. For anatomical structures, entity for representing an anatomical elements was introduced and the spatial relationship between the entity and the adjacent structures was represented. All the anatomical entities could be represented by this method. We verified that three thousand diseases could be represented by this top-level ontology framework.
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