Iwazaki Research Group

Medical AI & Biomedical Informatics

Research Group / Project Team

Medical AI & Biomedical Informatics

The Iwazaki Research Group brings together collaborative research activities in medical artificial intelligence, biomedical informatics, clinical natural language processing, and computational pathology. Junya Iwazaki, Ph.D. serves as Principal Investigator of competitively funded JSPS KAKENHI research projects and leads the current KAKENHI project 25K15335. The funded project team includes three Co-Investigators whose participation and institutional affiliations are independently documented in the NII KAKEN database.

Current Project

Active Competitive Research Project

Development of natural language processing technology enabling the creation of an integrated database of nationwide electronic medical record information

Principal Investigator
Junya Iwazaki, Ph.D.
Project No.
25K15335
Category
JSPS KAKENHI — Grant-in-Aid for Scientific Research (C)
Project period
April 2025 – March 2028
Research area
Life, health and medical informatics
Keywords
Medical AI · Natural Language Processing · Machine Learning · Electronic Medical Records

Project 25K15335 was awarded while Junya Iwazaki was affiliated with RIKEN. RIKEN is his former institution; he subsequently moved to Tohoku University, where he currently serves as Lecturer while continuing to lead this active project as Principal Investigator.

View the official KAKEN project record →

Project Team

Principal Investigator

Junya Iwazaki, Ph.D.

Lecturer, Tohoku University Graduate School of Medicine

Co-Investigator

Eichi Takaya

Assistant, Tohoku University Hospital / Part-time Lecturer, Tohoku University Graduate School of Medicine

Research

Medical AI & Biomedical Informatics

Machine-learning methods for integrating and analyzing heterogeneous clinical and biomedical data.

Clinical Natural Language Processing

Natural language processing for extracting, structuring, and integrating information from electronic medical records.

Computational Pathology

AI-based analysis of histopathology images, including multimodal and generative approaches.

Spatial & Multimodal Biology

Computational approaches connecting tissue morphology, spatial molecular measurements, and biological context.

Official Records