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New AI Tool Can Predict Cancer Patients' Survival Chances Using A Selfie, Suggests Study

Trained on over 40 million facial photos, the new AI tool estimates biological age from a single selfie and predicts how likely cancer patients are to survive treatment., Health, Times Now AI face scan in a clinical setting. Doctors have developed an artificial intelligence (AI) tool that can predict a cancer patient's chances of survival from just one photograph of their face. The system was built by experts at Mass General Brigham, a

By the Truvace desk1 min read1 sourceJournalismTRV-2026-2060· cite & verify
New AI Tool Can Predict Cancer Patients' Survival Chances Using A Selfie, Suggests Study

In brief

Researchers at Mass General Brigham have built an artificial intelligence system that analyzes a single photograph of a person's face. From that image it estimates biological age and predicts how likely a cancer patient is to survive treatment.

The approach could give clinicians a quick prognostic signal drawn from an ordinary image. The supplied excerpt is cut off, so it does not show how well the tool performs, which patients were tested, or whether it has been used in routine care.

Main points

  1. The tool was trained on more than 40 million facial photographs.
  2. It estimates biological age from a single selfie.
  3. It predicts how likely cancer patients are to survive treatment.
  4. The system was built by experts at Mass General Brigham.

The gain

An AI model trained on a very large set of face images can turn one selfie into a biological-age estimate and a forecast of whether a cancer patient will survive treatment.

The rundown

The article, published by Times Now in October 2026, describes the work as a study suggesting that a face image can carry information about a cancer patient's outlook. It presents the tool as developed by doctors.

The reported inputs and outputs are simple: one photo goes in, and the model returns a biological-age estimate and a survival-likelihood prediction for patients undergoing cancer treatment.

The accompanying image caption places the technology in a clinical setting, but the available text gives no accuracy figures, validation details, or deployment status.

Sources

  1. JournalismTimes Now2026-10-20

The debate