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A research team at Mass General Brigham developed the foundation AI model FAHR-Face, trained on more than 40 million facial photographs, and derived from it FAHR-FaceAge, which estimates biological age, and FAHR-FaceSurvival, which directly predicts the survival risk of cancer patients. FAHR-FaceSurvival was trained on 34,363 facial photographs of cancer patients; among patients in the highest 10% predicted mortality risk range, about half died within 90 days, compared with about 2% in the lowest 10% range, and the adjusted hazard ratio for the highest-risk group relative to the lowest-risk group was 3.23. The study also found that radiotherapy patients whose faces appeared at least 5 years older than their actual age had a 21% higher risk of death. The results have been published in The Lancet Digital Health, but the specific physiological signals identified by the model remain unclear, and the training population came mainly from high-income countries.
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Mass General Brigham team study: AI looks at faces to predict survival risk of cancer patientsDevelopments
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Oct 27
36Kr · AI
Mass General Brigham team study: AI looks at faces to predict survival risk of cancer patients
A team from Mass General Brigham in the United States published a study in The Lancet Digital Health, using facial photos of more than 34,000 cancer patients to train AI to predict mortality risk. In a held-out test of 3,820 people, among the 122 with the highest scores, 64 died within 90 days, while among the 975 with the lowest scores, only 20 died. Another version used photos of more than 38,000 radiotherapy patients to estimate biological age; those judged to "look more than 5 years older than their actual age" had a 21% higher mortality risk. The team has launched a research website for the public to upload selfies to estimate biological age, and stated that the results are for research only and are not diagnostic.
Oct 26
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Mass General Brigham develops the FAHR-Face model to predict survival risk of cancer patients using facial photos
A research team at Mass General Brigham, a healthcare system in Massachusetts, USA, developed the foundation AI model FAHR-Face, trained on more than 40 million facial photos, and derived FAHR-FaceAge for estimating biological age and FAHR-FaceSurvival for directly predicting the survival risk of cancer patients. FAHR-FaceSurvival was trained on 34,363 facial photos of cancer patients; among patients predicted to be in the highest 10% risk interval for death, about half died within 90 days, compared with about 2% in the lowest 10% interval, and the adjusted hazard ratio of the highest-risk group relative to the lowest-risk group was 3.23. The study also found that radiotherapy patients whose faces looked at least 5 years older than their actual age had a 21% higher risk of death. The results have been published in The Lancet Digital Health, but the specific physiological signals identified by the model remain unclear, and the training population mainly comes from high-income countries.