An AI is already able to find facial cues that could predict cancer survivalResearchers at Mass General Brigham have developed an AI tool called 'FAHR-Face' that uses facial recognition to predict cancer patients' survival rates and biological age. The system was trained using over 40 million facial images and can analyze simple photographs to determine health indicators. Two complementary tools were created: 'FAHR-FaceAge,' which estimates biological age more accurately than previous algorithms, and 'FAHR-FaceSurvival,' which predicts survival outcomes based on facial features. The study, published in Lancet Digital Health, highlights the potential for facial-based health assessments to support personalized treatment decisions, though they emphasize that such tools should not replace medical judgment. Researchers noted that lifestyle factors like smoking, drug use, and excessive alcohol consumption correlate with accelerated facial aging.
Bias read (Center): The article discusses technological advancements in healthcare without taking a stance on political issues. It presents research findings objectively, focusing on the development and application of AI in medical diagnostics.
They train an AI with over 40 million faces to identify in a photograph signals associated with the survival of cancer patientsResearchers at Mass General Brigham in Boston have developed an AI model called FAHR-Face, trained on over 40 million facial images, to extract health indicators from facial features. This system includes two models: FAHR-FaceAge, which estimates biological age more accurately than previous algorithms, and FAHR-FaceSurvival, designed to predict cancer patient survival rates based on facial characteristics. Analysis of over 38,000 cancer patients undergoing radiation therapy showed that those appearing five or more years older than their chronological age had a 21% higher risk of death during follow-up, while those looking younger had a 17% lower risk. Lifestyle factors such as smoking, drug use, and excessive alcohol consumption were linked to accelerated facial aging. The AI demonstrated robustness against variations in posture, lighting, expression, makeup, and even plastic surgery, except for rhinoplasty.
Bias read (Center): The article discusses technological advancements in AI for medical prediction, focusing on scientific research and health applications. There is no political framing, controversy, or ideological emphasis. The content remains strictly technical and neutral.
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