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Biomedical Data Science Lab
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A lab that brings machine learning for interpreting data that changes over time to real-world problems in medicine and chemistry.
AboutAbout the lab
Using AI to read data that unfolds over time.
The Biomedical Data Science Lab conducts research on applying artificial intelligence and machine learning to real-world problems, with a particular focus on time-series data processing.
Much of the data in the world contains information about the flow of time, but because of problem-specific background knowledge and noise, no established techniques exist yet.
Through real-world problems, the lab develops techniques to solve them.
According to its department page, the lab carries out research and development together with the Big Data Medical Science group (Professor Yasushi Okuno).
Key terms
- Time-series data
- Data recorded in chronological order, such as changes in heart rate or test values
- Machine learning
- Technology that lets computers learn rules and patterns from data
- Electronic medical record
- An electronic record of a patient's medical care, kept at a hospital
- Pretraining
- Training a model in advance on large amounts of data so that it can also be used for tasks with little data
ResearchResearch themes
The lab aims to apply machine learning techniques to real-world problems in medicine and chemistry.
*Illustrative imageDeep models that learn time series
The lab develops deep learning methods that learn the dynamics of data changing over time while preserving properties such as stability. It also works on estimating patient conditions from electronic medical records.
AI that predicts chemical reactions
The lab develops an AI foundation model for organic chemical reactions. By pretraining on large amounts of reaction data, it proposes a model that can accurately predict chemical reactions even with little data.
MembersFaculty
- Associate ProfessorRyosuke Kojima
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: “Principles of machine learning” Langs, G., Röhrich, S., Hofmanninger, J. et al. / CC BY 4.0 (cropped)
- Deep models that learn time series: “060731 logistic map time series 2” CommodiCast (talk) (Uploads) / Public domain (cropped)
- Related lab (Big Data Medical Science Lab): “Eqiadwmf 9060” RobH / CC BY-SA 3.0 (cropped)
- Related lab (Brain Function Rehabilitation Lab): “Occupational therapist helping a client create a job resume to send out to future employers” Mangionekd / CC BY-SA 4.0 (cropped)
- Related lab (Palliative Care Nursing Lab): “Marie Curie Palliative Care Institute Liverpool” Vanbasten 23 / CC BY-SA 3.0 (cropped)
- Related lab (Clinical Cognitive Neuroscience Lab): “Motor imagery” User:Decety / Public domain (cropped)
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