CVD Risk
The widespread adoption of smartwatches offers an unprecedented opportunity to observe CVD-relevant lifestyle and physiology continuously. However, despite strong evidence in the literature, these rich RWD (real-world data) streams are not currently used in care pathways, leaving a significant translational gap between consumer technology and clinical practice.
Therefore, we aim to develop, evaluate, and prepare for deployment of an agentic-AI platform that transforms raw consumer-grade DBMs (digital biomarkers) into continuous, clinically validated cardiovascular-risk scores and insights. We aim to achieve this, through a combination of (1) utilising the existing evidence in the literature, linking DBMs to CVD, and (2) developing our own proprietary CVD insights engines. In both cases, we aim to build a modern UX to connect care teams, patients, and latest state of real-world data/evidence in CVD care, with a special focus on DBMs.