US Mass General Brigham Team Develops AI Model That Predicts Cancer Death Risk from Face Photos

Researchers at Mass General Brigham in the United States recently published a new study in The Lancet Digital Health introducing FAHR-Face, an artificial intelligence model capable of predicting a cancer patient's risk of dying from a single facial photograph. Led by radiation oncologist Ray Mak and his colleagues, the study aims to address the subjectivity inherent in traditional clinical assessments.

Mak noted that medical students are trained to form an impression of a patient's health by observing them, a 'clinical intuition' that directly influences treatment plans such as surgery, chemotherapy, or radiation. However, this assessment is inherently subjective. FAHR-Face attempts to convert this subjective impression into objective data. The team first allowed the algorithm to 'learn' from 40 million facial images without a specific task, then fine-tuned it to perform two functions: estimating biological age and predicting survival odds for cancer patients.

Test results revealed surprising accuracy. In a test group of 3,820 cancer patients, 64 out of the 122 individuals with the highest risk scores died within 90 days of having their photo taken, accounting for more than half. In a larger separate test group of over 38,000 cancer patients, those who appeared older than their chronological age also had a higher risk of dying. The researchers stated this is the first report of an AI algorithm that can directly predict cancer patient survival from a simple face photograph.