AI Tool FaceAge Can Predict Biological Age from a Selfie

Doctors often rely on their intuition to assess a patient’s age, which can impact medical decisions. However, a new deep learning algorithm called FaceAge is changing the game by accurately determining a person’s biological age based on a simple headshot.

Trained on tens of thousands of photographs, FaceAge has shown promising results in cancer care. It revealed that cancer patients, on average, appear five years older biologically than their healthy counterparts. This information can help doctors tailor treatments to individual patients, ensuring they receive the most appropriate care.

For example, a 75-year-old with a biological age of 65 may be better suited for aggressive treatment, while a 60-year-old with a biological age of 70 could benefit from a gentler approach. This personalized approach could also be applied to decisions regarding heart surgery, hip replacements, and end-of-life care.

Sharper Lens on Frailty

FaceAge offers a non-invasive way to assess biological age, taking into account factors like genetics, lifestyle choices, and stress. By analyzing a simple selfie, the algorithm can provide valuable insights into an individual’s aging process.

The model was trained on a vast dataset of portraits of presumed-healthy adults over 60 and tested on cancer patients. It was found that cancer patients appeared almost five years older biologically than their actual age, with higher FaceAge scores predicting worse survival outcomes.

Interestingly, FaceAge prioritizes subtle facial changes over traditional signs of aging like gray hair or balding. This unique approach has proven to be more accurate than human assessments, improving doctors’ ability to make informed decisions about patient care.

Bias and Ethics Guardrails

As with any AI tool, FaceAge is being scrutinized for potential biases and ethical implications. While initial tests show no significant racial bias, ongoing research aims to ensure the algorithm’s fairness and accuracy across diverse populations.

There are also concerns about how FaceAge data could be misused by insurers or employers to assess risk. Ethical considerations are paramount, and the researchers are committed to ensuring that the technology is used responsibly for the benefit of patients.

Ultimately, FaceAge has the potential to revolutionize personalized medicine by providing valuable insights into biological age. As the researchers continue to refine the algorithm, there is hope that it will pave the way for more tailored and effective healthcare interventions.

© Agence France-Presse