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A research team at Mass General Brigham has developed an artificial intelligence tool that predicts the survival odds of cancer patients from a single facial photo, with the related study published in The Lancet Digital Health. The team trained the FAHR-Face foundation model and fine-tuned it into FAHR-FaceAge, which estimates biological age, and FAHR-FaceSurvival, which predicts survival risk in cancer patients; the models were trained on more than 40 million facial photos of people of different ethnicities and ages. In testing on 3,820 cancer patients, 64 of the 122 people (52.5%) in the highest survival-risk score bracket (0.9-1.0) died within 90 days of the photo being taken, while among the 975 people in the lowest bracket (0.0-0.1), the 90-day mortality rate was only 2.1%. Other reports note that among cancer patients receiving radiotherapy in the United States, those whose faces looked 5 or more years older than their actual age had a 21% higher risk of death over an average four-year follow-up period. The researchers say this is the first demonstration that an AI model can predict cancer survival directly from a photo, but they stress that the tool is intended to help doctors assess patients' physiological reserve, not to replace doctors' judgment, and that more research is needed before it is widely used.
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Research team develops AI tool that predicts cancer patient survival from a facial photo alone
Source:The Guardian Technology
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Oct 21
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Mass General Brigham team publishes FAHR-Face study in The Lancet Digital Health, using facial photos to predict mortality risk in cancer patients
The U.S. Mass General Brigham health care system developed the FAHR-Face model, which identifies differences in mortality risk among cancer patients using only a single facial photograph; the study was published on October 20 in The Lancet Digital Health. Among 3,820 cancer patients who did not participate in training, 64 of the 122 people rated by the model as extremely high risk died within 90 days after the photo was taken, while only 20 of the 975 people with scores between 0 and 0.1 died, a rate of 2.1%. The study also conducted external validation using 4,892 patients at the Maastro radiotherapy center in the Netherlands and obtained similar results, but the model cannot yet be used directly in clinical practice.
Oct 20
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The Guardian Technology
Mass General Brigham study: a single selfie can predict cancer patients' survival rates
A Mass General Brigham team developed two tools, FAHR-FaceAge and FAHR-FaceSurvival, which can estimate biological age from a single facial photo and directly predict survival outcomes in cancer patients. The study was published in Lancet Digital Health, and the model was trained on more than 40 million facial photos of people of different ethnicities and ages. Among cancer patients receiving radiotherapy in the United States, those who looked 5 years or more older than their actual age had a 21% higher risk of death over an average four-year follow-up period, while those who looked 5 years or more younger had a 17% lower risk. The researchers said this is the first demonstration that an AI model can directly predict cancer survival from a photo, but stressed that more research is needed before widespread use.