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Updated: Feb 4, 2026

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Behavioral Phenotyping of Murine Disease Models with the Integrated Behavioral Station INBEST
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Digital phenotyping and ASCVD risk: An exploratory cross-sectional analysis using online behavioral data
Lauren Southwick1,2, Neil K R Sehgal3,4, Dena Torrente1
1Department of Emergency Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA.
American Heart Journal Plus : Cardiology Research and Practice
|February 3, 2026
Summary
Social media data may offer insights into cardiovascular disease (CVD) risk, potentially complementing traditional clinical assessments. Further research is needed to confirm the association between online behaviors and heart health outcomes.
Area of Science:
- Digital Health
- Cardiovascular Medicine
- Social Epidemiology
Background:
- Cardiovascular disease (CVD) risk is traditionally assessed using clinical factors.
- Social media platforms generate vast amounts of user data reflecting behaviors and social determinants.
- The utility of social media data for predicting CVD risk beyond established models is largely unexplored.
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