The Bitemporal Lens Model—toward a holistic approach to chronic disease prevention with digital biomarkers

Abstract

We introduce the Bitemporal Lens Model, a comprehensive methodology for chronic disease prevention using digital biomarkers. The Bitemporal Lens Model integrates the change-point model, focusing on critical disease-specific parameters, and the recurrent-pattern model, emphasizing lifestyle and behavioral patterns, for early risk identification. Results-By incorporating both the change-point and recurrent-pattern models, the Bitemporal Lens Model offers a comprehensive approach to preventive healthcare, enabling a more nuanced understanding of individual health trajectories, demonstrated through its application in cardiovascular disease prevention. We explore the benefits of the Bitemporal Lens Model, highlighting its capacity for personalized risk assessment through the integration of two distinct lenses. We also acknowledge challenges associated with handling intricate data across dual temporal dimensions, maintaining data integrity, and addressing ethical concerns pertaining to privacy and data protection. The Bitemporal Lens Model presents a novel approach to enhancing preventive healthcare effectiveness.

Jinjoo Shim

Digital Health Data Scientist

My research interests is to advance digital healthcare through AI/ML and data science.