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AI Frontier Medical Innovation Lab (Center for Innovative and Applied Medicine)
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A lab that uses AI and statistics to explore how the genome and lifestyle relate to disease.
AboutAbout the lab
Estimating disease risk from the genome and lifestyle
The AI Frontier Medical Innovation lab studies how to estimate disease risk from large-scale data on the genome and lifestyle.
The lab applies statistical methods, artificial intelligence and machine learning, and theories of genetics and genomic science to medical and genomic information collected in genome cohorts, biobanks, and medical institutions in Japan and abroad.
Recently, the lab has also focused on applying large language models to electronic medical records and on research into genomic language models.
On the lab's website, it is introduced under the name "Risk Statistical Analysis Room."
Key terms
- Genome cohort study
- Research that examines differences in the genes (DNA) and lifestyles of many people to explore their relationship with disease
- Statistical genetics
- A field that combines genetics and statistics. It uses statistical methods to examine how genetic differences relate to disease and physical constitution
- Large language model
- An artificial intelligence that learns from large amounts of text and handles language. It is applied to uses such as making use of the text in electronic medical records
NewsLab news
View More ↗ResearchResearch themes
The lab aims to identify, through genome analysis experiments and theory, the genes (DNA) and lifestyle factors involved in lifestyle-related diseases such as cancer, heart disease, and diabetes, and to connect these findings to prevention and treatment. Using statistical genetics methods, it studies the cohorts of the Tohoku Medical Megabank Organization.
*Illustrative imageSearching for gene–lifestyle interactions
The lab examines differences in individuals' genes (DNA) and uses statistical genetics to find lifestyle factors that interact with them, such as smoking, drinking, diet, and exercise. This approach is called genome cohort research. If risk factors are found, it may lead to prevention methods and new treatments.
*Illustrative imageMany factors, few samples
Advances in experimental technology have caused the number of factors to examine to grow explosively, while the number of samples has plateaued, so conventional statistical methods cannot give accurate answers. The lab holds that the key to solving this difficult problem lies in statistical genetics, which combines genetics and statistics.
MembersFaculty
- ProfessorGen Tamiya
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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.
- Top image: “Séquençage du génome d'une microalgue au laboratoire GENALG (Ifremer )” Stephane Lesbats (IFREMER, Pôle Images, Centre Bretagne - ZI de la Pointe du Diable - CS Plouzané, France) / CC BY 4.0 (cropped)
- Searching for gene–lifestyle interactions: “DNA Double Helix by NHGRI” National Human Genome Research Institute / Public domain (cropped)
- Many factors, few samples: “Microarray Comparative Genomic Hybridisation” National Cancer Institute / Public domain (cropped)
- Related lab (Biomarker Discovery Lab (Tohoku Medical Megabank Organization)): “Blood test samples” Fumikas Sagisavas / CC0 (cropped)
- Related lab (Clinical Epidemiology Lab (Tohoku Medical Megabank Organization)): “Mother and newborn baby, Moscow, Russia” Vyacheslav Argenberg / CC BY 4.0 (cropped)
- Related lab (Regional Oral Health Science Lab (Tohoku Medical Megabank Organization)): “Set of dental tools and instruments on a table in a clinic during a procedure” Shixart1985 / CC BY 2.0 (cropped)
- Related lab (Integrative Genomic Predictive Medicine Lab (Tohoku Medical Megabank Organization)): “Illumina NextSeq 500” Konrad Förstner / CC BY 2.0 (cropped)
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