Biomedical Informatics
Bioinformatics

Biomedical Informatics
Bioinformatics

Associate Professor

Takeshi Imai

1. Research

The Division of Biomedical Informatics focuses on interdisciplinary research where medicine, engineering, and informatics intersect, with a particular emphasis on the development and clinical application of medical artificial intelligence (AI) systems.

Specifically, we develop computer-aided diagnostic and clinical decision support systems, medical safety support technologies, medical knowledge discovery and utilization from large-scale clinical databases, and the standardization of medical information. Our approach utilizes a hybrid methodology that combines knowledge reasoning techniques based on clinical knowledge databases with advanced information processing technologies, such as machine learning and Large Language Model (LLM)-based natural language processing (NLP).

Furthermore, we work in close collaboration with the Department of Biomedical Informatics at the Graduate School of Medicine and the Department of Planning, Information and Management at the University Hospital. Our goal is to promote the secondary use of real-world clinical data and to ensure that research outcomes are effectively fed back into clinical practice.

Our previous research initiatives include:

  • Construction and utilization of clinical knowledge databases.
  • Development of diagnostic support systems in the field of internal medicine.
  • Automated structuring and knowledge discovery from medical documents using NLP.
  • High-precision electrocardiogram (ECG) analysis via deep learning.
  • Application of AI to mental healthcare.

In the development of medical AI, the social return of research results is a vital perspective. Consequently, we are actively engaged in social implementation, aiming to release our findings as accessible services for real-world users.

Projects

  1. Development of clinical large language models (LLMs) and their applications in diagnostic and clinical decision support.
  2. Construction of clinical ontologies and establishment of their theoretical foundations.
  3. Development of clinical text analysis, knowledge discovery, and knowledge structuring methods using natural language processing.
  4. Application of knowledge reasoning technologies to diagnostic support systems.
  5. Development of clinical information analysis techniques utilizing deep learning and ontologies.
  6. Development and standardization of healthcare information models.

2. Publications

  1. Tsukiji Y, Kataoka S, Itokazu M, Nagai R, Imai T. Evaluating Encoder and Decoder Models for Extended Clinical Concept Recognition in Japanese Clinical Texts: A Comparative Study with Weighted Soft Matching. J Med Internet Res. 2026 Mar 17. doi: 10.2196/78681. Epub ahead of print. PMID: 41879043.
  2. Ogasawara R, Imai T, Takeda K, Nakagome K. Machine-Learning-Based Prediction of Suicide Risk Using Preliminary Questionnaire and Consultation Text. Stud Health Technol Inform. 2025 Aug 7;329:861-865. doi: 10.3233/SHTI250962. PMID: 40775980.
  3. Tanaka T, Katayama T, Imai T. Predicting the effects of drugs and unveiling their mechanisms of action using an Interpretable Pharmacodynamic Mechanism Knowledge Graph (IPM-KG). Computers in Biology and Medicine, Epub 2024 November. doi: https://doi.org/10.1016/j.compbiomed.2024.109419.
  4. Cai C, Imai T, Hasumi E, Fujiu K. One-shot screening: Utilization of a two-dimensional convolutional neural network for automatic detection of left ventricular hypertrophy using electrocardiograms. Comput Methods Programs Biomed. 2024 Feb 25;247:108097. doi: 10.1016/j.cmpb.2024.108097. Epub ahead of print. PMID: 38428250.
  5. Yokota S, Doi S, Fukuhara M, Mitani T, Nagashima S, Gonoi W, Imai T, Ohe K. Application program to detect unrecognized information regarding malignant tumors in radiology reports. Health and Technology, Epub 2022 Dec. doi: https://doi.org/10.1007/s12553-022-00724-0
  6. Shiokawa Y, Mori N, Sakusabe T, Imai T, Watanabe H, Kimura M. Medical Image Sharing in Japan. J Digit Imaging. 2022 Aug;35(4):772-784. doi: 10.1007/s10278- 022-00675-y. Epub 2022 Aug 22. PMID: 35995897; PMCID: PMC9395812.
  7. Aoki M, Yokota S, Kagawa R, Shinohara E, Imai T, Ohe K. Automatic Classification of Electronic Nursing Narrative Records Based on Japanese Standard Terminology for Nursing. Comput Inform Nurs. 2021 May 12;39(11):828-834.
  8. Ma X, Imai T, Shinohara E, Kasai S, Kato K, Kagawa R, Ohe K. EHR2CCAS: A framework for mapping EHR to disease knowledge presenting causal chain of disorders – chronic kidney disease example. J Biomed Inform. 2021 Mar;115:103692. doi: 10.1016/j.jbi.2021.103692. Epub 2021 Feb 4. PMID: 33548543.
  9. Iwai S, Mitani T, Hayakawa J, Shinohara E, Imai T, Kawazoe Y, Ohe K. Development of Graph-Based Algorithm for Differentiating Pathophysiological Conditions. Applied Medical Informatics. 2020;42(2):107-117.
  10. Mitani T, Doi S, Yokota S, Imai T, Ohe K. Highly accurate and explainable detection of specimen mix-up using a machine learning model. Clin Chem Lab Med. 2020 Feb 25;58(3):375-383.
  11. Hayakawa M, Imai T, Kawazoe Y, Kozaki K, Ohe K. Auto-Generated Physiological Chain Data for an Ontological Framework for Pharmacology and Mechanism of Action to Determine Suspected Drugs in Cases of Dysuria. Drug Saf. 2019 Sep;42(9):1055-1069.
  12. Kagawa R, Shinohara E, Imai T, Kawazoe Y, Ohe K. Bias of Inaccurate Disease Mentions in Electronic Health Record-based Phenotyping. Int J Med Inform. 2019 Apr;124:90-96.
  13. Ishihara S, Fujiu K, Imai T. An analysis of one-shot screening methods of ECG with different types of 2-D CNN. Journal of Neuroscience and Biomedical Engineering, 2019, 1(1): 1-9.
  14. Ma X, Imai T, Shinohara E, Sakurai R, Kozaki K, Ohe K. A Semi-Automatic Framework to Identify Abnormal States in EHR Narratives. Stud Health Technol Inform. 2017;245:910-914.
  15. Kagawa R, Kawazoe Y, Shinohara E, Imai T, Ohe K. The Impact of “Possible Patients” on Phenotyping Algorithms: Electronic Phenotype Algorithms Can Only Be Reproduced by Sharing Detailed Annotation Criteria. Stud Health Technol Inform. 2017;245:432-436.
  16. Iwai S, Kawazoe Y, Imai T, Ohe K. Effects of Implementing a Tree Model of Diagnosis into a Bayesian Diagnostic Inference System. Stud Health Technol Inform. 2017;245:882-886.
  17. Kozaki K, Yamagata Y, Mizoguchi R, Imai T, Ohe K. Disease Compass- a navigation system for disease knowledge based on ontology and linked data techniques. J Biomed Semantics. 2017 Jun 19;8(1):22. doi: 10.1186/s13326-017-0132-2.
  18. Kagawa R, Kawazoe Y, Ida Y, Shinohara E, Tanaka K, Imai T, Ohe K. Development of Type 2 Diabetes Mellitus Phenotyping Framework Using Expert Knowledge and Machine Learning Approach. J Diabetes Sci Technol. 2017 Jul;11(4):791-799. doi: 10.1177/1932296816681584. Epub 2016 Dec 7.
  19. Imai T, Shinohara E, Kajino M, Sakurai R, Ohe K, Kozaki K, Mizoguchi R. An Ontological Framework for Representing Topological Information in Human Anatomy. In Proc. of International Conference on Biomedical Ontology and BioCreative (ICBO-BioCreative 2016), Corvallis, USA, August 1-4, 2016. CEUR Workshop Proceedings, ISSN 1613-0073, available online at CEUR-WS.org/Vol-1747/, 2016.
  20. Kawazoe Y, Imai T, Ohe K, A Querying Method over RDF-ized Health Level Seven v2.5 Messages Using Life Science Knowledge Resources, JMIR Med Inform 2016;4(2):e12.
  21. Kozaki K, Yamagata Y, Mizoguchi R, Imai T and Ohe K. Disease Compass – Navigation System for Disease Knowledge based on Ontology and Linked Data Techniques. In Proc. of International Conference on Biomedical Ontology (ICBO 2015), Lisbon, Portugal, pp.77-81, July 27-30, 2015.
  22. Yamagata Y, Kozaki K, Imai T, Ohe K, Mizoguchi R. Towards the Integration of Abnormality in Diseases. In Proc. of the 5th International Conference on Biomedical Ontology (ICBO2014), Houston, USA, pp.7-12, October 6-9, 2014.
  23. Kozaki K, Yamagata Y, Imai T, Ohe K, Mizoguchi R. Publishing a Disease Ontologies as Linked Data. In Proc. of Third Joint International Semantic Technology Conference (JIST2013), South Korea, November 28-30, 2013. Lecture Notes in Computer Science Volume 8388, 2014, pp. 110-128.
  24. 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.
  25. Yamagata Y, Kou H, Kozaki K, Mizoguchi R, Imai T, Ohe K. Ontological Model of Abnormal States and its Application in the Medical Domain. In Proc. of the 4th International Conference on Biomedical Ontology (ICBO 2013), Montreal, Qc, Canada, pp.22-27, July 8-9, 2013.
  26. 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.
  27. Yoshida Y, Imai T, Ohe K. The trends in EMR and CPOE adoption in Japan under the national strategy. Int J Med Inform. 2013 Oct;82(10):1004-11.
  28. 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.
  29. Yamagata Y, Kou H, Kozaki K, Mizoguchi R, Imai T, Ohe K. Ontological Modeling of Interoperable Abnormal States. In Proc. of Second Joint International Semantic Technology Conference (JIST 2012), Nara, Japan, December 2-4, 2012. Lecture Notes in Computer Science Volume 7774, 2013, pp 33-48.
  30. Kozaki K, Mizoguchi R, Imai T, Ohe K. Identity Tracking of a Disease as a Causal Chain. In Proc. of the 3rd International Conference on Biomedical Ontology (ICBO 2012), KR-MED Series, July 21-25, 2012, Graz, Austria, Ronald Cornet ans Robert Stevens (eds.), CEUR Workshop Proceedings, ISSN 1613-0073, available online at CEUR-WS.org/Vol-897/,pp.131-136, 2012.
  31. Kozaki K, Mizoguchi R, Imai T, Ohe K. A Consideration on Identity of Diseases. Proc. of the Fifth Interdisciplinary Ontology Meeting, pp.75-80, Tokyo, Japan, February 23-24, 2012.
  32. Mizoguchi R, Kozaki K, Kou H, Yamagata Y, Imai T, Waki K, Ohe K. River Flow Model of Diseases. Proc. of International Conference on Biomedical Ontology 2011 (ICBO2011), pp.63-70, 2011.
  33. Kou H, Ohta M, Zhou J, Kozaki K, Mizoguchi R, Imai T, Ohe K. Development of Fundamental Technologies for Better Understanding of Clinical Medical Ontologies. Proc. of International Conference on Knowledge Engineering and Ontology Development (KEOD 2010),pp.235-240, 2010.
  34. 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.
  35. 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.
  36. Imai T, Kou H, Zhou J, Kozaki K, Mizoguchi R, Ohe K. Japan Medical Ontology Development Project for Advanced Clinical Information Systems. Proc. Of 10th International HL7 Interoperability Conference 2009 (IHIC2009), pp.42-46, 2009.
  37. Mizoguchi R, Kou H, Zhou J, Kozaki K, Imai T, Ohe K. An Advanced Clinical Ontology. Proc. Of International Conference on Biomedical Ontology 2009 (ICBO2009), pp.119-122, 2009.
  38. Aramaki E, Imai T, Miyo K, Ohe K. Orthographic Disambiguation Incorporating Transliterated Probability. Proc. of International Joint Conference on Natural Language Processing (IJCNLP2008), pp.48-55, 2008.
  39. Aramaki E, Imai T, Miyo K, Ohe K. Support Vector Machine Based Orthographic Disambiguation. Proc. of the Conference on Theoretical and Methodological Issues in Machine Translation (TMI2007). pp.21-30, 2007.
  40. Aramaki E, Imai T, Miyo K, Ohe K. UTH: Semantic Relation Classification using Physical Sizes. The Association for Computational Linguistics (ACL2007) Workshop on Semantic Evaluations (SemEval 2007). pp.464-7, 2007.
  41. Imai T, Aramaki E, Kajino M, Miyo K, Onogi Y, Ohe K. Finding malignant findings from radiological reports using medical attributes and syntactic information. Stud Health Technol Inform. 2007;129(Pt 1):540-4.
  42. 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.
  43. Aramaki E, Imai T, Miyo K, Ohe K. Automatic Deidentification by using Sentence Features and Label Consistency. Proceedings i2b2 Workshop on Challenges in Natural Language Processing for Clinical Data, 2006.
  44. Aramaki E, Imai T, Miyo K, Ohe K. Patient Status Classification by using Rule based Sentence Extraction and BM25-kNN based Classifier. Proceedings i2b2 Workshop on Challenges in Natural Language Processing for Clinical Data, 2006.
  45. Aramaki E, Imai T, Kashiwagi M, Kajino M, Miyo K, Ohe K. Toward Medical Ontology using Natural Language Processing. Proc. of OntoLex2005, IJCNLP’05. pp.53-8, 2005.
  46. Imai T, Onogi Y. Extracting Numerical Measurements and Temporal Coordinates from Japanese Radiological Reports. Proc. of SPIE Medical Imaging 2004;5371: pp.268-76, 2004.

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