US researchers say an AI tool may soon help doctors assess how ill a patient is by analyzing a single photograph of their face - because nothing says modern medicine like reducing your prognosis to a profile pic. The tool, trained on millions of healthy faces and 35,000 photos of cancer patients, estimates survival by scrutinizing features near the eyes, according to scientists. It's a long way from hospital-ready, but the goal is to help doctors recommend the right treatments.

The preliminary findings are published in the Lancet Digital Health. Dubbed 'FaceSurvival,' the AI suggests the area under the eyes and around the bridge of the nose are the most vital facial regions for estimating how long a patient might have left. These metrics held across many cancer types, varying in severity, including cancers that had spread to the bones or brain. The patients, from the US and the Netherlands, were mostly in their 50s or 60s - but some were children, and others in their 90s.

Doctors already examine patients and run comprehensive tests to judge illness and prognosis. The AI tool, which has a patent application pending, is designed to assist - not replace - them. Lead researcher Dr. Raymond Mak of Mass General Brigham in Boston explained: 'As the population ages, physicians need better ways to estimate physical reserve and frailty before recommending intensive treatments such as radiation, surgery or systemic therapy. Our goal is to make face photograph-based health assessment more quantitative, consistent and scalable so it can support personalised treatment decisions rather than replace physician judgment.'

Mak and colleagues are also evaluating an AI tool for predicting biological age - how old someone looks, as opposed to their birthday age. The 'FaceAge' tool suggests the skin below the nose and near the mouth (nasolabial folds and marionette lines), plus the forehead (frown lines), temples (crows' feet) and cheeks are good indicators of how fast we age. Some lifestyle habits speed that up, like heavy alcohol use, drug use and smoking. Mak says the tool was 'surprisingly consistent' across common real-world photos despite variations in pose, lighting, facial expression and make-up. 'It was also stable across most tested plastic surgery procedures, with only a small shift observed after rhinoplasty,' he noted.

But the researchers stress they need much more data and photos, particularly from diverse ethnic groups, to determine how well the tools work. They are still very much under development. The team is inviting the public to take part and receive a personalised biological age estimate by uploading their own facial photo.

Prof Miroslaw Bober, an expert in video processing and machine learning at the University of Surrey, says claims that the tool could track ageing or lifestyle changes over time would be 'premature.' 'This is a promising proof of concept, but it is not ready for clinical use,' he said. 'The tool still needs testing against doctors' own judgement and across different hospitals and patient groups.' And he warned: 'Predicting an outcome is not the same as explaining it.'