Eyes may be the window to the soul, but a person’s biological age could be reflected in their facial characteristics. Investigators from Mass General Brigham developed a deep learning algorithm called FaceAge that uses a photo of a person’s face to predict biological age and survival outcomes for patients with cancer. They found that patients with cancer, on average, had a higher FaceAge than those without and appeared about five years older than their chronological age.

Older FaceAge predictions were associated with worse overall survival outcomes across multiple cancer types. They also found that FaceAge outperformed clinicians in predicting short-term life expectancies of patients receiving palliative radiotherapy. We can use artificial intelligence (AI) to estimate a person’s biological age from face pictures, and our study shows that information can be clinically meaningful, said co-senior and corresponding author Hugo Aerts, PhD, director of the Artificial Intelligence in Medicine (AIM) program at Mass General Brigham.

This work demonstrates that a photo like a simple selfie contains important information that could help to inform clinical decision-making and care plans for patients and clinicians. How old someone looks compared to their chronological age really matters individuals with FaceAges that are younger than their chronological ages do significantly better after cancer therapy.

When patients walk into exam rooms, their appearance may give physicians clues about their overall health and vitality. Those intuitive assessments combined with a patient’s chronological age, in addition to many other biological measures, may help determine the best course of treatment. However, like anyone, physicians may have biases about a person’s age that may influence them, fueling a need for more objective, predictive measures to inform care decisions.

Source: https://www.massgeneralbrigham.org/en/about/newsroom/press-releases/ai-face-photos-tool-estimate-age-predict-cancer-outcomes