AI facial health recognition tools help physicians assess age and survival risk to guide personalized treatment
Researchers are using AI tools to analyze simple facial photographs to determine key indicators of a person's health. Mass General Brigham researchers built FAHR-Face (Foundation Artificial Intelligence for Health Recognition), a large AI foundation model trained on over 40 million face images.
Researchers at Mass General Brigham are leveraging advanced artificial intelligence to analyze facial photographs and gain insights into patients' health. They developed the Foundation Artificial Intelligence for Health Recognition (FAHR-Face), a large AI model trained on over 40 million images. This foundation model forms the basis for two complementary tools: FAHR-FaceAge and FAHR-FaceSurvival.
FAHR-FaceAge estimates patients' biological age with greater precision than previous algorithms, while FAHR-FaceSurvival predicts survival outcomes in cancer patients based on facial photographs alone.
The study, published in Lancet Digital Health, found that the difference between a patient's estimated age and their actual age was linked to survival, indicating the potential of these tools to guide personalized treatment decisions. The researchers also discovered that lifestyle factors, such as heavy alcohol use, drug use, and smoking, can influence how old a person's face appears.
Despite being derived from the same foundation model, the two tools captured different and complementary information about patients' health, and their combined predictions improved survival-model fit in an external validation cohort of cancer patients.
Written by urgent.news from Medical Xpress's reporting — not their text. Machine-written — may contain errors; check the original before relying on it.
