FaceAge, an AI model revealed in The Lancet Digital Health, estimates biological age from selfies, demonstrating strong accuracy in predicting mortality risks. Trained with a dataset of nearly 59,000 images, it assesses not just facial wrinkles but deeper indicators of aging. In a study involving over 6,000 cancer patients, those who appeared older than their actual age showed an increased likelihood of earlier death. When FaceAge's evaluations complemented doctors' assessments, survival prediction accuracy improved significantly, indicating the potential of facial analysis as a new vital sign.
Traditionally, vital signs are physiological checkpoints, but with FaceAge, a photograph may provide equally vital information about a patient's biological status and mortality risks.
FaceAge was trained on nearly 59,000 images, allowing it to detect subtle markers of agingâtransforming facial assessment from novelty apps to a major health insight.
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