Laboratories / Div. of Research Resources & Support

Biomedical Informatics /
Section of Bioinformatics

Associate Professor: Takeshi Imai

1. Research
Targeting biomedical research support using information technologies, the division performs management of the research network and the central servers of the Graduate School of Medicine, and also performs researches on knowledge infrastructure, knowledge processing techniques, and their application to clinical practice.
For example, with an increase in the medical care information being compiled electronically, the significance of secondary use of medical information for advanced knowledge processing, such as information retrieval, data mining, automated coding and decision support systems, has emerged as a practical concern. For those purposes, several knowledge bases and fundamental techniques in the medical informatics domain are required, such as terminologies and ontologies, natural language processing, machine reasoning and so on.
The division actively collaborates with the Department of Medical Informatics and Economics, Graduate School of Medicine at the University of Tokyo, and the Department of Planning, Information and Management at the University of Tokyo Hospital, to develop such knowledge resources and processing techniques, and to develop methodologies for applying those techniques to clinical practice. Our activities also include international standardization of healthcare information models at ISO TC215 (health informatics) WG3.
  1. Development of the Japanese medical ontology and its theoretical basis.
  2. Development of methodologies for mapping medical terminologies and other text resources to medical ontologies.
  3. Natural language processing and its application to the medical domain.
  4. Development of machine reasoning techniques and their application to clinical decision support systems.
  5. Standardization of information models of health concept representation.
2. Publications
  1. Yamagata Y, Kozaki K, Imai T, Ohe K, Mizoguchi R. An ontological modeling approach for abnormal states and its application in the medical domain. J Biomed Semantics. 2014 May 21;5:23. doi: 10.1186/2041-1480-5-23. eCollection 2014.
  2. Kozaki K, Yamagata Y, Imai T, Ohe K, Mizoguchi R. Publishing a Disease Ontologies as Linked Data. Semantic Technology Lecture Notes in Computer Science Volume 8388, 2014, pp. 110-128.
  3. Imai T, Hayakawa M, Ohe K. Development of Description Framework of Pharmacodynamics Ontology and Its Application to Possible Drug-drug Interaction Reasoning. Stud Health Technol Inform. 2013;192:567-71.
  4. Yoshida Y, Imai T, Ohe K. The trends in EMR and CPOE adoption in Japan under the national strategy. Int J Med Inform. 2013 Aug 8. pii: S1386-5056(13)00159-7. doi: 10.1016/j.ijmedinf.2013.07.004. [Epub ahead of print]
  5. Shinohara EY, Aramaki E, Imai T, Miura Y, Tonoike M, Ohkuma T, Masuichi H, Ohe K. An easily implemented method for abbreviation expansion for the medical domain in Japanese text. A preliminary study. Methods Inf Med. 2013;52(1):51-61.
  6. Imai T, Kajino M, Sato M, Ohe K. Development of structured ICD-10 and its application to computer-assisted ICD coding. Stud Health Technol Inform. 2010;160(Pt 2):1080-4.
  7. Yamada E, Aramaki E, Imai T, Ohe K. Internal structure of a disease name and its application for ICD coding. Stud Health Technol Inform. 2010;160(Pt 2):1010-4.
  8. Imai T, Aramaki E, Kajino M, Miyo K, Ohe K. Finding malignant findings from radiological reports using medical attributes and syntactic information. Stud Health Technol Inform. 2007;129(Pt 1):540-4.
  9. Aramaki E, Imai T, Kajino M, Miyo K, Ohe K. Statistical selector of the best multiple ICD-coding method. Stud Health Technol Inform. 2007;129(Pt 1):645-9.