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Medical Informatics Lab
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A lab that aims to gain knowledge by collecting and analyzing high-quality medical data.
AboutAbout the lab
Connecting patients, healthcare professionals, and data toward trustworthy medical AI
The Medical Informatics Lab studies the collection of high-quality real-world data and the acquisition of knowledge from that data.
Working with the Department of Medical Informatics at the university hospital, the lab aims to build high-quality medical databases, acquire medical knowledge through machine learning, and apply it clinically.
The faculty hold concurrent appointments in the Department of Medical Informatics at Osaka University Hospital and are in charge of the hospital's information system.
The lab accepts students from any background, not only from medicine but also from engineering, science, and the humanities and social sciences.
Key terms
- Data warehouse
- A database in which the clinical data needed for clinical research are transferred and managed for analysis
- OCR-net
- Osaka Clinical Research Network. A mechanism that collects data by linking with the electronic medical records of partner medical institutions
- Dynamic consent
- A method of obtaining individual consent for each research project
- Natural language processing
- Technology for processing text written by people with computers. Here it is used to extract information from imaging reports
NewsLab news
A paper comparing large language models and knowledge distillation for extracting MedDRA/J search queries
A paper on natural language processing for automatically classifying the clinical T category of lung cancer from chest CT reports
ResearchResearch themes
The lab aims to collect high-quality real-world data and gain knowledge from it, with research spanning ICT, multi-center studies, PHR, natural language processing, machine learning, and diagnostic support. Working with the Department of Medical Informatics at the university hospital, it aims to build high-quality medical databases, acquire medical knowledge through machine learning, and apply it clinically.
Secondary use of clinical data
The lab has moved the data needed for clinical research into an analytical database (data warehouse) for management, and has worked on research in pharmacoepidemiology and health economics. It has shown that, when the necessary data are available, a study simulating a prospective clinical study can be completed in about one week.
*Illustrative imageData collection for multi-center clinical research
To support multi-center clinical research at the core clinical research hospital, the lab is building mechanisms that link with the electronic medical records of OCR-net partner medical institutions and efficiently collect electronic case report forms, medical images, and clinical samples. It has also built a multi-center common database that collects insurance claims data and electronic medical record data using common SQL.
*Illustrative imageMedical information banks and PHR
The lab conducts demonstration studies of medical information banks, a type of Personal Health Record (PHR) in which individuals manage their own health and medical information. According to the lab, when patients and researchers are connected through an information bank, research can be conducted by obtaining individual consent for each research project (dynamic consent).
*Illustrative imageMachine learning and natural language processing
The lab works on research that gains knowledge through machine learning methods. Research on automated diagnosis and prognosis prediction through deep learning using OCR-net medical images and clinical information is possible, and the lab uses natural language processing to extract information on lesions and their locations from imaging reports for use in clinical research.
MembersFaculty
The members of the Medical Informatics Lab consist of faculty members, visiting faculty members, researchers, staff, specialized technical staff, technical assistants, secretaries, doctoral students, and research students.As of 2026
- ProfessorToshihiro Takeda
- Associate ProfessorYoshiki Okada
- Project Assistant ProfessorShozo Konishi
- Project Assistant ProfessorKento Sugimoto
- Project Assistant ProfessorKeisuke Nakajima
- Assistant Professor, Endowed ChairSeiya Wada
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Report an errorAbout the images
The top and research theme images are illustrative and were not taken at the lab. They are cropped from Wikimedia Commons images. Cropped CC BY-SA images are provided under the same CC BY-SA license as the original (version shown on each line).
- Top image: “Hope Family Health High Speed Broadband to Patients (20180927-RD-LSC-0093)” USDAgov / Public domain (cropped)
- Data collection for multi-center clinical research: “Servers in a Rack” Abigor / CC BY-SA 3.0 (cropped)
- Medical information banks and PHR: “Personal Child Health Record - 'Red Book'” Royal College of Paediatrics and Child Health / Public domain (cropped)
- Machine learning and natural language processing: “Normal posteroanterior (PA) chest radiograph (X-ray)” Mikael Häggström / CC0 (cropped)
- Related lab (Advanced AI Medicine Lab): “CSIRO ScienceImage 2465 Sequencing DNA” Health Sciences and Nutrition, CSIRO / CC BY 3.0 (cropped)
- Related lab (Gastroenterological Surgery I Lab): “Breast surgery in operating room” Tyler Frew MD / CC BY-SA 4.0 (cropped)
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