LAB LOGA page on LabLog, a review site (not the lab's official page)
Digital Health Lab
Machine-translated · View original
The lab analyzes digital health information with AI and epidemiology to solve problems in medicine and health care.
AboutAbout the lab
Solving problems in medicine and health care with health data and AI.
The Digital Health Lab analyzes a wide range of digitized health information, aiming to solve problems in medicine and health care.
The data it works with include electronic medical records, insurance claims (receipts), information from mobile apps and biosensors, images and audio, and genomic and omics data.
In addition to conventional epidemiological and statistical methods, the lab uses AI analysis techniques such as machine learning.
The lab welcomes students who have mastered the basics of epidemiology and biostatistics and want to take on the analysis of new types of medical big data, as well as the development and implementation of new tools.
Key terms
- Insurance claims (receipts)
- Itemized statements of medical fees that medical institutions submit to insurers for reimbursement. They are used in analysis as records of the care provided and its cost.
- Epidemiology
- The study of how diseases occur and what causes them, using data from populations.
- Omics
- A general term for information obtained by comprehensively examining molecules in the body, starting with the genome.
NewsLab news
Paper on herpes zoster risk in breast cancer survivors published in Breast Cancer Research
Paper by Prof. Iwagami and colleagues on a prediction model for sleep apnea syndrome published in Sleep and Breathing
Review paper on sleep-related indicators published in Environmental Health and Preventive Medicine
Paper by a visiting researcher published in Frontiers in Pharmacology
Paper on endometrial cancer risk in breast cancer survivors published in Breast Cancer
ResearchResearch themes
Digital health is a relatively new field within medicine. The lab applies epidemiological and statistical methods and AI analysis techniques to a wide range of digitized health information, with the goal of solving problems in medicine and health care that span from the human body to society.
View More ↗
MembersFaculty
The members of the Digital Health Lab are faculty, visiting professors, PhD students, visiting researchers, and alumni of the lab.As of 2026
- ProfessorMasao Iwagami
- Assistant ProfessorChitose Kawamura
VoicesStudent voices
Ratings and reviews reflect the experiences of individual current or former students, not the lab's official views. Whether a lab has reviews, or how many, says nothing about the lab itself.
Students who take part in an interview may receive a thank-you gift worth ¥1,000, regardless of what they say.
Student ratings (0 students)
--
--
--
--
--
--
Student voices answer questions like these
- What's great about this lab?
- What did you learn after joining?
- What's the vibe, and what is the professor like?
- Who is this lab for?
- Where do graduates go?
Your experience can help younger students choose their lab. Your name won't be shown.
Write a lab reviewAnonymous · Your draft is saved if you stopRelatedLabs similar to Digital Health Lab
Life Course Epidemiology LabSchool of Medicine and Health Sciences, School of MedicineClinical and pharmacoepidemiology using claims data (receipt…
Neurology LabSchool of Medicine and Health Sciences, School of MedicineTranslational research starting from genomic and omics data …
Nephrology LabSchool of Medicine and Health Sciences, School of MedicinePathology, immunology, biochemistry, physiology, molecular b…
Microbiome Ecology (Metabologenomics) LabSchool of Medicine and Health Sciences, School of MedicineGut design for disease prevention and treatment: metagenomic…The information on this page is compiled by the LabLog team from the lab's public information and interviews. For corrections or removal requests, please contact LabLog, not the lab.
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: “Ordinateur portable de Wikimedia France faisant tourner le logiciel Linto et un dashboard développé pour l'occasion pour la transcription en temps réel (49071)” Don-vip / CC BY-SA 4.0 (cropped)
- AI analysis of diverse health information: “BalticServers data center” BalticServers.com / CC BY-SA 3.0 (cropped)
- Related lab (Life Course Epidemiology Lab): “Children playing on skipping rope” Amuzujoe / CC BY-SA 4.0 (cropped)
- Related lab (Neurology Lab): “Automated confocal image reader” Neil Emans IPK / CC BY-SA 3.0 (cropped)
- Related lab (Nephrology Lab): “Hemodialysis equipment” U3061292 / CC BY-SA 3.0 (cropped)
- Related lab (Microbiome Ecology (Metabologenomics) Lab): “Anaerobic chamber ( )” Oak Ridge National Laboratory / CC BY 2.0 (cropped)
About LabLog
LabLog is a lab review app for students only. Student members at each university interview students in labs and publish what they say. Student voices can only be read by students who sign up with a university email address. Operated by bestiee Inc.
Learn more about LabLog ↗Search engines and AI may reference the basic lab info and rating summaries on this page and the description of LabLog. Student voices are for student members only. Automated collection by programs (scraping, or input to or training of AI) is prohibited under Article 8 of the Terms of Service. If you need data for research or analysis, please contact us.