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Medical Data Science Lab
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A lab that aims to solve problems in medicine and healthcare using large-scale medical data.
AboutAbout the lab
Using data to solve healthcare problems.
The Medical Data Science lab uses large-scale observational data to tackle a wide range of problems in medicine and healthcare.
Newly established in 2026, the lab traces its origins to the chair of Hospital Administration, the first of its kind established in Japan, in fiscal 1952 (Showa 27).
The data it uses include registries such as the National Clinical Database and insurance claims databases.
The lab also works on the social implementation of its research results, using databases and data-driven methods.
Key terms
- Clinical epidemiology
- A discipline that statistically examines the characteristics of diseases and treatments based on data from groups of patients
- Registry
- A database that collects and accumulates information on diseases, surgeries, and the like using predetermined items
- Claims database (receipt database)
- A database compiling information from medical fee statements (receipts) that medical institutions submit to insurers for reimbursement
ResearchResearch themes
The Medical Data Science lab appropriately utilizes large-scale observational data to address various issues in medicine and healthcare. The main data sources are registries such as the National Clinical Database and insurance claims databases.
*Illustrative imageClinical epidemiology of large-scale observational data
The lab appropriately utilizes various kinds of large-scale observational data to advance clinical epidemiology research and health services research.
*Illustrative imageVerifying how data are generated and whether they are valid
The lab works to ensure that the process by which large-scale observational data are created is appropriate, and verifies whether the resulting data are valid.
*Illustrative imageEvaluating and improving the quality of care
The lab applies large-scale observational data to evaluate the quality of care and to lead to its improvement.
*Illustrative imageData analysis with new methods
The lab works to advance methods for analyzing large-scale data using new approaches.
MembersFaculty
- ProfessorHiroyuki Yamamoto
- LecturerArata Takahashi
VoicesStudent voices
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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: “A technician enters data into a computer at Gorgas Army Hospital - DPLA - 2300987e22c18aeeb904c6c80c26a36e” Department of Defense. American Forces Information Service. Defense Visual Information Center. 1994 / Public domain (cropped)
- Clinical epidemiology of large-scale observational data: “Stethoscope and Laptop Computer - Nci-vol-9713-300” Daniel Sone (photographer) / Public domain (cropped)
- Verifying how data are generated and whether they are valid: “Data center roof” Rsparks3 / CC0 (cropped)
- Evaluating and improving the quality of care: “- Equipment in the corridor, Evelyn Ward, Northwick Park Hospital, London” Kolforn (Kolforn) I'd appreciate if you could mail me ( ) if you want to use this picture out of the Wikimedia project scope. This file is licensed under the Creative Commons Attribution-Share Alike 4.0 International license. You are free: to share – to copy, distribute and transmit the work to remix – to adapt the work Under the following conditions: attribution – You must give appropriate credit, provide a link to the license, and indicate if changes were made. You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use. share alike – If you remix, transform, or build upon the material, you must distribute your contributions under the same or compatible license as the original.https://creativecommons.org/licenses/by-sa/4.0CC BY-SA 4.0 Creative Commons Attribution-Share Alike 4.0 truetrue / CC BY-SA 4.0 (cropped)
- Data analysis with new methods: “Network graph visualization showing bibliography and keywords” Ecpp / CC BY-SA 4.0 (cropped)
- Related lab (Medical Statistics Lab): “NQuery Sample Size Software - Power Analysis Software” DeBurca01 / CC BY-SA 4.0 (cropped)
- Related lab (Emergency Medicine Lab): “Pioneer Valley Ambulance 214” Mangocove / CC BY-SA 4.0 (cropped)
- Related lab (Artificial Intelligence in Medical Science Lab (Affiliated Center for Creative and Applied Medical Research)): “Graphics Processing Unit” Nick Stathas / CC BY-SA 4.0 (cropped)
- Related lab (Health Behavioral Epidemiology Lab (Tohoku Medical Megabank Organization)): “A community health worker conducting a survey in the Korail slum, Bangladesh ( )” DFID - UK Department for International Development / CC BY 2.0 (cropped)
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