TOPページ > Project Associate Professor Yoshimasa Kawazoe M.D, Ph.D

Project Associate Professor Yoshimasa Kawazoe M.D, Ph.D

English | Japanese

Faculty Positions: 

  • Project Associate Professor, Artificial Intelligence in Healthcare, Graduate School of Medicine.

Research Interests:

  • Natural Language Processing in Medicine.
  • High-throughput Phenotyping from Electronic Health Records.
  • Knowledge representation and processing for a new exploration of clinical and translational research.
  • Standardization in medical informatics.

Educations: 

  • March 2009 Ph.D. in Medical Informatics and Economics, The University of Tokyo, Japan
  • March 2001 M.D. in School of Medicine, University of Yamanashi, Japan

Professional Training and Employment: 

  • 2018 7-: Project Associate Professor, Artificial Intelligence in Healthcare, Graduate School of Medicine, The University of Tokyo.
  • 2016 12- 2020 03: Researcher, JST PRESTO.
  • 2016 09 – 2018 06: Assistant Professor, Graduate School of Medicine and Faculty of Medicine.
  • 2015 07 – 2016 04: Visiting Scholar, Department of Biomedical Informatics and Medical Education, University of Washington, Seattle, WA.
  • 2012 05 – 2016 08: Research Associate, The University of Tokyo Hospital, Department of Planning, Information and Management.
  • 2011 – 2012: Project Research Associate The University of Tokyo Hospital, Department of Planning, Information and Management.
  • 2009 – 2011: Senior Resident The Cancer Institute Hospital Of JFCR, Department of Cancer Clinical Treatment.
  • 2009  – 2010: Project Researcher The University of Tokyo Hospital, Department of Planning, Information and Management.
  • 2001 – 2004: Junior Resident Tokyo Metropolitan Police Hospital, Department of Internal Medicine.

BIME@University of Washington, Seattle, WA

Societies: 

  • Japanese Association for Medical Informatics
  • The Japanese Society for Artificial Intelligence
  • The Japanese Society of Internal Medicine

Awards

  • Best Paper Award in The 28th Joint Conference on Medical Informatics (2008)

Research Grants (JST, JSPS)

  1. 2021-2024: Grant-in-Aid for Challenging Research (Exploratory). Grant Number 21K19633.
  2. 2020-2023: Grant-in-Aid for Scientific Research (B). Grant Number 20H04279.
  3. 2018-2023: Grant-in-Aid for Scientific Research (A). Grant Number 18H04076.
  4. 2016-2019: JST PRESTO. Grant Number JPMJPR1654.
  5. 2016-2018: Grant-in-Aid for Scientific Research (C). Grant Number 16K09161.
  6. 2015-2017: Grants-in-Aid for Scientific Research (B). Grant Number 15H04793.
  7. 2013-2015: Grants-in-Aid for Young Scientist (B). Grant Number 25870156.

Publication Journals

  1. Kawazoe Y, Shimamoto K, Shibata D, Shinohara E, Kawaguchi H, Yamamoto T. Impact of a Clinical Text–Based Fall Prediction Model on Preventing Extended Hospital Stays for Elderly Inpatients: Model Development and Performance Evaluation. JMIR Med Inform 2022;10(7):e37913
  2. Hayakawa J, Seki T, Kawazoe Y, Ohe K. Pathway importance by graph convolutional network and Shapley additive explanations in gene expression phenotype of diffuse large B-cell lymphoma. PLoS One. 2022 Jun 24;17(6):e0269570.
  3. Kawazoe Y, Shibata D, Shinohara E, Aramaki E, Ohe K. A clinical specific BERT developed using a huge Japanese clinical text corpus. PLoS One. 2021 Nov 9;16(11):e0259763.
  4. Seki T, Kawazoe Y, Ohe K. Machine learning-based prediction of in-hospital mortality using admission laboratory data: A retrospective, single-site study using electronic health record data. PLoS ONE. 2021;16(2): e0246640.
  5. Yamaguchi R, Kawazoe Y, Shimamoto K, Emiko Shinohara, Tatsuo Tsukamoto, Yukako Shintani-Domoto, Hajime Nagasu, Hiroshi Uozaki, Tetsuo Ushiku, Masaomi Nangaku, Naoki Kashihara, Akira Shimizu, Michio, Nagata, Kazuhiko Ohe. Glomerular classification using convolutional neural networks based on defined annotation criteria and concordance evaluation among clinicians. Kidney Int Rep. 2020 Dec 13;6(3):716-726.
  6. 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. Vol. 42, No. 2/2020.
  7. 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 Safety. 2019,42:1055–1069.
  8. 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.
  9. Kawazoe Y, Shimamoto K, Yamaguchi R, Shintani-Domoto Y, Uozaki H, Fukayama M, Ohe K. Faster R-CNN-Based Glomerular Detection in Multistained Human Whole Slide Images. Journal of Imaging. 2018; 4(7):91.
  10. Rina Kagawa, Yoshimasa Kawazoe, Emiko Shinohara, Takeshi Imai, Kazuhiko Ohe. The impact of “possible patients” on phenotyping algorithms: Electronic phenotype algorithms can only be reproduced by sharing detailed annotation criteria. Stud Health Technol Inform. 245, pp.432-436, 2017.
  11. Satoshi Iwai, Yoshimasa Kawazoe, Takeshi Imai, Kazuhiko Ohe. Effects of implementing tree model of diagnosis into a Bayesian diagnostic inference system. Stud Health Technol Inform. 245, pp.882-886, 2017.
  12. 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 2016 Dec 7.
  13. 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.
  14. Hiroki Osumi, Eiji Shinozaki, Masahiko Osako, Yoshimasa Kawazoe, Masaru Oba, Takaharu Misaka, Takashi Goto, Hitomi Kamo, Mitsukuni Suenaga, Yosuke Kumekawa, Mariko Ogura, Masato Ozaka, Satoshi Matsusaka, Keisho Chin, Kiyohiko Hatake, Nobuyuki Mizunuma. Cetuximab treatment for metastatic colorectal cancer with KRAS p.G13D mutations improves progression-free survival. Molecular and Clinical Oncology 3, no.5 (2015): 1053-1057.
  15. Kawazoe Y, Miyo K, Kurahashi I, Sakurai R, Ohe K., Prediction based Threshold for Medication Alert. Stud Health Technol Inform. 2013;192:229-33.
  16. Oba M, Chin K, Kawazoe Y, Takagi K, Ogura M, Shinozaki E, Suenaga M, Matsusaka S, Mizunuma N, Hatake K. Availability of irinotecan in a second-line setting confers survival benefit to patients with advanced gastric cancer refractory to fluoropyrimidine-based regimens. Oncol Lett. 2011 Mar;2(2):247-251.
  17. Oba M, Chin K, Kawazoe Y, Takagi K, Ogura M, Shinozaki E, Suenaga M, Matsusaka S, Mizunuma N, Hatake K. Irinotecan monotherapy offers advantage over combination therapy with irinotecan plus cisplatin in second-line setting for treatment of advanced gastric cancer following failure of fluoropyrimidine-based regimens. Oncol Lett. 2011 Mar;2(2):241-245.
  18. Kawazoe Y, Ohe K. An ontology-based mediator of clinical information for decision support systems: a prototype of a clinical alert system for prescription. Methods Inf Med. 2008;47(6):549-59.

Conference presentation

  1. Kenya Sakka, Kotaro Nakayama, Nisei Kimura, Taiki Inoue, Yusuke Iwasawa, Ryohei Yamaguchi, Yoshimasa Kawazoe, Kazuhiko Ohe, Yutaka Matsuo. Character-level Japanese Text Generation with Attention Mechanism for Chest Radiography Diagnosis. AAAI Workshop on Artificial Intelligence, February 7-8, 2020, New York, USA. https://arxiv.org/abs/2004.13846
  2. Rina Kagawa, Yoshimasa Kawazoe, Emiko Shinohara, Takeshi Imai, Kazuhiko Ohe. The impact of “possible patients” on phenotyping algorithms: Electronic phenotype algorithms can only be reproduced by sharing detailed annotation criteria. MEDINFO2017: The 16th World Congress on Medical and Health Informatics. Aug 2017, Hanzou, China.
  3. Satoshi Iwai, Yoshimasa Kawazoe, Takeshi Imai, Kazuhiko Ohe. Effects of implementing tree model of diagnosis into a Bayesian diagnostic inference system. MEDINFO2017: The 16th World Congress on Medical and Health Informatics. Aug 2017, Hanzou, China.
  4. Kawazoe Y, Miyo K, Kurahashi I, Sakurai R, Ohe K. Prediction based Threshold for Medication Alert. Stud Health Technol Inform. 2013;192:229-33.
  5. Shinohara E, Tatsukawa A, Kawazoe Y, Imai T, Ohe K. A Qualitative Model for Physiology: Apart from Function and Abnormality. Stud Health Technol Inform. 2013;192:984.
  6. Tatsukawa A, Shinohara E, Kawazoe Y, Imai T, Ohe K. An Analysis of the OpenEHR Archetype Semantics Based on a Typed Lambda Theory. Stud Health Technol Inform. 2013;192:990.
  7. Miyo K, Kawazoe Y, Yamaguchi I, Tatsukawa A, Ohe K. Evaluation of a Context-based Prescription Alert System: A Clinical Perspective. Stud Health Technol Inform. 2013;192:1030.
  8. Ishii M, Kawazoe Y, Tatsukawa A, Ohe K. A method for handling multi-institutional HL7 data on Hadoop in the cloud. Big Data 2013 Conference, Apr 2013, Brisbane, Australia.
  9. Osako M, Kawazoe Y, Mizunuma N, Gotoh T, Misaka T, Oba M, Shinozaki E, Suenaga M, Matsusaka S, Hatake K. Cetuximab Treatment for Metastatic Colorectal Cancer With KRAS p.G13D Mutation may Improve Progression-free Survival in Japanese Patients. Eur J Cancer, 47:395-396, Sept 2011.

Skills

  1. Programming language/Statistical Analysis: Java, Python, R
  2. Database: RDBMS, RDF Database
  3. Natural language Processing