Data-driven model predicts heart failure risk
Healthcare in Europe
Last updated: April 25, 2026
Researchers at the University of Tartu, led by Laura Lõo, have developed novel models to predict disease risk pre-symptomatically. These models integrate multi-omics data and lifestyle factors, offering a proactive approach to healthcare. The goal is to enable early interventions and personalized prevention strategies.
- Key Facts: The new models utilize a combination of multi-omics data (genomics, proteomics, metabolomics) and lifestyle information.
- This data integration allows for the identification of individuals at high risk of developing specific diseases before any clinical symptoms manifest.
- The research aims to shift healthcare towards a more predictive and preventive paradigm.
- Early identification of risk factors can facilitate timely lifestyle modifications or medical interventions.
- This approach has the potential to reduce disease burden and improve patient outcomes.
- The models are developed with international collaboration, enhancing their robustness and applicability.
- The ultimate objective is to contribute to personalized medicine and population health management.
