AI Predicts Cardiopulmonary Age From Chest X-Rays
A study published in The Journals of Gerontology reports that a deep learning model called CXR-Age estimated biological aging from chest X-rays in 2,097 adults in the Project Baseline Health Study. CXR-Age correlated with coronary calcium, worse lung function, frailty, and elevated neuroinflammation-linked proteins, while Horvath Age and DNAm PhenoAge showed weaker associations. The authors conclude imaging-derived age may better indicate cardiopulmonary aging and help identify at-risk individuals before symptoms.
Key Points
- 1Demonstrates CXR-Age predicts biological age from chest X-rays in 2,097 Project Baseline participants
- 2Shows stronger associations with coronary calcium, lung function decline, frailty versus DNA epigenetic clocks
- 3Enables clinicians to identify preclinical cardiopulmonary aging risk, supporting preventive personalized interventions
Scoring Rationale
Peer-reviewed study shows strong CXR-Age associations with cardiopulmonary markers, but requires broader clinical validation and longitudinal outcome data.
Sources
Public references used for this report.
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