AI can now predict cancer survival by analysing an individual's selfie, Lancet study finds
ETimes May 10, 2025 05:39 PM

AI and cancer might sound like an odd pair, but they're actually teaming up in game-changing ways. From scanning selfies to spotting tumors in scans faster than ever, artificial intelligence is stepping up in the fight against cancer. One new study even shows that AI can guess your biological age just by analyzing your face—and that might help predict how well you’ll respond to cancer treatment. Pretty wild, right? While it’s not replacing doctors anytime soon, AI is becoming a powerful tool that’s helping save lives, one algorithm at a time. The future of cancer care just got smarter.

Researchers at Mass General Brigham have developed an AI tool named FaceAge, which analyzes facial features to estimate a person's biological age. This estimation provides valuable information about a patient's overall health and potential cancer survival outcomes. In a study involving over 6,000 cancer patients, those whose FaceAge appeared older than their actual age tended to have poorer survival rates.

All about FaceAgeFaceAge was trained on nearly 59,000 photos of healthy individuals to learn how facial features correlate with biological aging. When applied to cancer patients, the tool could predict survival outcomes more accurately than clinicians alone. For instance, when doctors used FaceAge alongside their assessments, the accuracy of predicting six-month survival for patients undergoing palliative radiotherapy improved from 61% to 80%.

Biological age refers to how old your body appears based on various health indicators, as opposed to your chronological age. Factors like genetics, lifestyle, and environmental exposures influence biological aging. FaceAge taps into this by evaluating facial cues—such as skin texture and facial lines—to estimate biological age, providing insights into a patient's health status and resilience against diseases like cancer.

How can this revolutionize patient care
The integration of tools like FaceAge into clinical settings could revolutionize patient care. By providing an objective measure of biological age, doctors can better tailor treatment plans, identify patients who may need more aggressive interventions, and improve communication about prognosis. Moreover, it empowers patients with more information about their health, potentially motivating lifestyle changes to improve outcomes.

The researchers found: For example, a fit 75-year-old whose biological age is 10 years younger than their chronological age might tolerate and respond to treatment better and live longer than a 60-year-old whose biological age is 10 years older than their chronological age.

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