| Title: | Big Data and Artificial Intelligence in Cardio-Metabolic Disease |
| Lead Institution: | University of Science and Technology of China |
| Principal investigator: |
Application 148816
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About
Scientific rationale: Cardio-metabolic disorders, encompassing a spectrum of conditions from heart diseases to metabolic dysfunctions, pose significant challenges in modern healthcare. Often silently progressing, these disorders can evade early detection, amplifying the subsequent health implications and socio-economic burdens. The emergence of advanced omics technologies has heralded a new era in precision medicine, providing novel insights into the molecular foundations of diseases. Aims: Our research seeks to revolutionize the landscape of early diagnosis and intervention. By harnessing advanced technologies and vast data sources, complemented by the power of artificial intelligence, we aim to gain a deeper understanding of these disorders. Integrating diverse streams of health data - from lifestyle nuances and genetic blueprints to proteomic and metabolic fingerprints, complemented by medical imaging - we aspire to construct a comprehensive tableau of cardio-metabolic health. Project duration: The duration of the project will be for 36 months. Public health impact: The cornerstone of our approach is the application of AI. AI's computational prowess will synthesize this multi-modal data, enhancing our capability to unearth subtle early markers and predict potential disease trajectories. Such AI-driven insights promise not only precision but also timeliness in intervention, two critical facets in managing such complex disorders. Our endeavor, rooted in this innovative confluence of multi-omics and AI, holds the promise to transform the paradigm of cardio-metabolic healthcare. By facilitating a deeper, more holistic understanding of disease mechanisms, we envision a future where personalized, proactive interventions become the norm, significantly mitigating the health and economic impacts of these disorders. In essence, our research stands at the crossroads of advanced technology and clinical expertise, aspiring to shape the future of cardio-metabolic healthcare.1 Publication
| Pub ID | Title | Author(s) | Year | Journal |
|---|---|---|---|---|
| 19982 | A multi-omics atlas of multisystem complications in type 2 diabetes reveals molecular signatures and improves risk prediction | Hongqiang Zhang (+11) | 2026 | Metabolism |
Enabling scientific discoveries that improve human health