| Title: | Machine learning to investigate musculoskeletal diseases and the impact of movement, physical measurements, comorbidities, demographics and self-recorded medical conditions. |
| Lead Institution: | MRI TUM - Technische Universität München |
| Principal investigator: |
Application 144927
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About
In the Department of Orthopaedics and Sports Orthopaedics and the Institute for AI and Informatics in Medicine at the Technical University of Munich, we are researching the integration of AI in medical areas in a multidisciplinary research team. The team includes experts from IT (especially AI specialists), orthopaedics, rehabilitation and prevention. We will use machine learning algorithms to explore health data. Our goal is to find out more about diseases that affect our bones and muscles. We also want to see how movement, physical traits and other illnesses people might have, where they come from and their own reports about their health play a role in these diseases. Bone and muscle diseases can really affect a person's quality of life. By understanding more about them, we hope we can figure out ways to spot these diseases early or even prevent them in some cases. We want to use the UK Biobank data because it's a vast collection of health information from many people, making it a treasure trove for researchers like us. After we finish, our findings could help doctors and health experts give better advice to the public about bone and muscle health. In the long run, this could lead to healthier lives for many and might even save on healthcare costs if fewer people end up needing treatment.1 Publication
| Pub ID | Title | Author(s) | Year | Journal |
|---|---|---|---|---|
| 17734 | Deep learning of wrist accelerometry from UK Biobank data identifies early movement signatures of knee osteoarthritis up to 5 years before diagnosis | Ricardo Smits Serena (+6) | 2026 | Knee Surgery Sports Traumatology Arthroscopy |
Enabling scientific discoveries that improve human health