Somerville, Mass.-based Mass General Brigham researchers built an AI foundation model, trained on more than 40 million face images, that estimates biological age and predicts cancer survival from a single photograph.
The model, called FAHR-Face, powers two tools detailed in a study published Oct. 19 in The Lancet Digital Health. FAHR-FaceAge estimates a patient’s biological age more accurately than prior algorithms. FAHR-FaceSurvival predicts survival outcomes directly from a face photo of a patient with cancer.
The gap between a patient’s FAHR-FaceAge and chronological age was independently linked to survival. The two tools’ predictions were only weakly correlated, and combining them improved survival-model fit in an external validation cohort of cancer patients.
Hugo Aerts, PhD, director of the Artificial Intelligence in Medicine program at Mass General Brigham, said the work is, to the team’s knowledge, “the first demonstration” that an AI model can directly predict cancer survival from a photograph, per an Oct. 19 news release.
Raymond Mak, MD, a radiation oncologist at Mass General Brigham Cancer Institute and the study’s corresponding author, said physicians need better ways to gauge frailty before recommending intensive treatments such as radiation, surgery or systemic therapy. The goal is to support personalized treatment decisions “rather than replace physician judgment,” Dr. Mak said.
FAHR-FaceAge held steady across variations in pose, lighting, facial expression and makeup, as well as most plastic surgery procedures, with a small shift after rhinoplasty. Heavy alcohol use, drug use and smoking were associated with looking biologically older.
Mass General Brigham has filed a U.S. provisional patent application on next-generation facial health algorithms and is expanding the research through a public online study approved by an institutional review board.
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