{
  "id": 15835651,
  "title": "Can an AI tool predict a cancer patient’s chances of survival from a single photo?",
  "url": "https://urgent.news/2026/10/21/can-an-ai-tool-predict-a-cancer-patients-chances-of-survival-from-a",
  "topic": "ai",
  "section": "AI",
  "published": "2026-10-21T02:13:59.000Z",
  "source": {
    "name": "The Indian Express",
    "slug": "the-indian-express",
    "url": "https://indianexpress.com/article/health-wellness/artificial-intelligence-ai-facial-photo-predicts-biological-age-cancer-survival-study-10930130/"
  },
  "original_language": "en",
  "account": "Researchers from Mass General Brigham have developed an AI model called FAHR-Face that can estimate biological age and predict survival chances in cancer patients based on a single facial photo. The model, which was trained on over 40 million publicly available facial images, uses two complementary tools - FAHR-FaceAge and FAHR-FaceSurvival - to assess biological age and predict survival prospects. Biological age, which reflects how a person appears in terms of age rather than chronological age, was found to be an important factor in predicting mortality risk. Patients with an estimated biological age at least five years older than their actual age had a 21% higher risk of death during an average follow-up of four years, while those with an estimated biological age at least five years younger had a 17% lower risk. The AI model also showed robust performance across various variations in facial photographs. The study's findings suggest that facial photographs could offer a non-invasive way to assess certain aspects of a patient's health and help inform treatment decisions. However, the technology still requires further validation before it can be used routinely in clinical practice.",
  "summary": null,
  "key_points": [
    "FAHR-Face AI model predicts cancer patients' survival from facial photos",
    "Biological age, not chronological age, crucial for mortality risk prediction",
    "Study validates non-invasive method for health assessment"
  ],
  "editors_take": null,
  "illustration": null,
  "coverage": {
    "outlets": 1,
    "also_reported_by": []
  },
  "ai_generated": true,
  "disclaimer": "Summaries, key points and the editor’s take are written by software from other outlets’ reporting and may contain errors — always check the linked original."
}