• FaceAge, an AI tool, estimates biological age from facial photos, potentially helping doctors personalize cancer treatment.
• The tool analyzes facial features like muscle mass around the temples to predict a patient's ability to withstand aggressive treatments.
• Researchers are conducting trials to validate FaceAge's accuracy, address biases, and explore its broader applications in medical decision-making.

Researchers at Mass General Brigham have created FaceAge, an AI-powered tool designed to estimate a person's biological age by analyzing facial photographs. This tool aims to provide doctors with a more objective assessment of a patient's health, particularly in determining their ability to withstand aggressive cancer treatments like chemotherapy and radiation. FaceAge analyzes subtle differences in facial features, such as muscle mass around the temples and soft tissue around the eyes and nose, to predict survival outcomes. The tool's development addresses the need for quantitative methods in assessing patient frailty and tailoring treatment plans.

• What: FaceAge is an AI tool that analyzes facial photos to estimate a person's biological age. It identifies subtle differences in facial features linked to aging, such as muscle mass loss and soft tissue changes.
• Who: Developed by scientists at Mass General Brigham, led by Dr. Ray Mak and Hugo Aerts. Key figures include Jay Ball, a cancer patient, and experts like Alpa Patel and Andrew Beam who provide external perspectives.
• When: The research was published in The Lancet Digital Health on Thursday. Development and testing are ongoing, with trials planned for patients with early-stage lung cancer.
• Where: Developed and tested at Mass General Brigham in Boston, MA. The tool is intended for use in clinical settings to aid treatment decisions.

FaceAge represents a novel application of AI in healthcare, offering a potentially low-cost and accessible tool for assessing patient health and predicting treatment outcomes. Its ability to estimate biological age from a simple facial photo could significantly aid doctors in making informed decisions, especially for older patients or those with complex medical conditions. However, the tool's accuracy and reliability are subject to ongoing research and validation. Concerns about biases, the influence of external factors like lighting and cosmetics, and the need for diverse datasets must be addressed before FaceAge can be widely adopted in clinical practice.

We don’t have a quantitative way to make that assessment right now. It’s a big missing tool.

There’s even basic questions, like, what kind of filter did you use? And how many megapixels was the photo that you took. So I think that there’s a lot that we have still yet to learn.

Face-based aging tools have “extraordinary potential” to help doctors quickly and inexpensively estimate how healthy their patients are, compared with existing tests

FaceAge is an innovative AI tool that holds promise for improving medical decision-making by estimating biological age from facial photos. While initial results are encouraging, ongoing trials and further research are crucial to validate its accuracy, address potential biases, and explore its full range of applications. The tool's success depends on refining its algorithms, expanding its datasets, and ensuring its ethical and responsible implementation in clinical settings.