| Title: | Integrative Deep Learning Analysis of UKBB Data: Bridging Genotypes, Medical Imaging, and Polygenic Scores for Precision Health Insights |
| Lead Institution: | Nanjing Medical University |
| Principal investigator: |
Application 144904
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About
What's the Goal? We're delving into vast health data, using cutting-edge computer techniques, to understand how our genes influence our health. Our mission is to reveal hidden connections between our genetic makeup and our well-being. Why This Research? Our genes hold secrets to our health, and while we've uncovered some, there's much more to explore. Advanced computing can give us a clearer picture, helping to better understand, treat, or even prevent diseases. Timeframe: We're setting out on this three-year journey, analyzing data, refining our tools, and drawing actionable insights. How Will Everyone Benefit? Spot Health Risks Early: Unraveling genetic clues can help doctors detect issues before they escalate. Personalized Care: Treatments can be tailored for each person, enhancing effectiveness. Empower Communities: With better health knowledge, people can make informed decisions for a healthier life. In Short: By blending advanced computing with health data, we're working towards personalized, effective healthcare for all.2 Publications
| Pub ID | Title | Author(s) | Year | Journal |
|---|---|---|---|---|
| 14102 | Integrating transcriptomic and polygenic risk scores to enhance predictive accuracy for ischemic stroke subtypes | Xuehong Cai (+8) | 2024 | Human Genetics |
| 14795 | Shared genetic architecture and bidirectional clinical risks within the psycho-metabolic nexus | Xiaonan Guo (+8) | 2024 | EBioMedicine |
Enabling scientific discoveries that improve human health