This AI predicts cancer survival chances by analyzing selfies.

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This AI predicts cancer survival chances by analyzing selfies.

Researchers at Mass General Brigham in the US created ‘FaceAge,’ an AI tool analyzing selfies to determine an individual’s “biological age,” aiding in health assessment and personalized cancer treatment. This method serves as an unbiased option to the subjective “eyeball test” doctors traditionally rely on.

The FaceAge tool uses deep learning algorithms to analyze facial features in a photo and estimate biological age, which indicates physiological condition rather than chronological age, offering insights into health. It was trained on 58,851 images of healthy people and tested on 6,000 cancer patients, showing promise in clinical applications.

Dr. Hugo Aerts emphasized the significance of a cost-effective AI tool that can monitor a person’s biological age continuously, stressing its potential to greatly impact healthcare by providing an easy and efficient way to track a patient’s health status over time.

In clinical evaluations, FaceAge demonstrated poorer survival rates for patients whose biological age exceeded their actual age, regardless of cancer type or gender. This effect was pronounced for those with a FaceAge over 85 years. Notably, when combined with clinician assessments, FaceAge enhanced the accuracy of predicting six-month survival for patients receiving palliative radiotherapy from 61% to 80%.

The use of facial photographs to determine biological age can guide treatment decisions. For example, a 75-year-old with a biological age of 65 may receive more intensive treatment than a 60-year-old with a biological age of 70, enhancing personalized cancer care strategies.

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