The tool of scan the faces to predict the biological age and the survival of cancer

A simple selfie could contain hidden clues to the biological era, and even how long they will live.

According to General Mass Brigham researchers, who developed a deep learning algorithm called Faceage.

Using a photo of someone’s face, the artificial intelligence tool generates predictions of the subject’s biological age, which is the rate they age instead of their chronological age.

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Faceage also predicts survival results for people with cancer, according to a MGB press release.

The AI ​​tool was trained at 58,851 photos of “alleged healthy individuals of public data sets,” said the statement.

To prove the accuracy of the tool, the researchers used it to analyze photos of 6,196 cancer patients taken before radiotherapy treatment.

Among people with cancer, the tool generated a higher biological age that was approximately five years higher than its chronological age.

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The researchers also tested the ability of the tool to predict the life expectancy of 100 people who receive palliative care based on their photos, then compared it to the predictions of 10 doctors. It was found that Faceage is more precise than doctors’ predictions.

The findings of the researchers were published in Lancet Digital Health.

“We can use artificial intelligence to estimate the biological age of a person of the facial images, and our study shows that the information can be clinically significant,” said the co-senior and corresponding author Hugo Aerts, PHD, director of the Artificial Intelligence Program in Medicine (AIM) in Mass General Brigham, in the launch.

“This work shows that a photo like a simple selfie contains important information that could help inform clinical decision making and care plans for patients and doctors,” he continued.

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“How old is someone compared to their chronological age is really important: people with facets that are younger than their chronological ages are significantly better after cancer therapy.”

The objective is that the tool helps eliminate any bias that can influence the care decisions of a doctor based on the perception of the appearance and age of a patient.

“While Faceage can overcome doctors in some survival predictions, human judgment should increase, not to cancel it.”

The researchers indicated that more research is needed before the tool could be implemented for clinical use.

Future studies will include different hospitals and cancer patients in several stages of the disease, according to the statement. Researchers will also evaluate Faceage to predict diseases, general health status and useful life.

“This opens the door to a new kingdom of discovery of biomarkers from photographs, and its potential goes far beyond cancer care or age prediction,” said the co-senior author Ray Mak, MD, a member of the Faculty in the AIM program in General Mass Brigham, in the statement.

“As we think more and more in different chronic diseases such as aging diseases, it becomes even more important to be able to precisely predict the trajectory of aging of an individual. I hope we can finally use this technology as an early detection system in a variety of applications, within a strong regulatory and ethical framework, to help save lives.”

ER doctor in AI

Dr. Harvey Castro, emergency medicine doctor certified by the National Board and speaker on artificial intelligence based in Dallas, Texas, did not participate in the development of Faceage, but shared his comments on the tool.

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“As an emergency and futuristic doctor, I see the promise and danger of AI tools as Faceage,” he told News Digital.

“What excites me is that Faceage structures the clinical instinct that we call the ‘eyeball test’, an intestinal sense of how sick someone looks. Now, automatic learning can quantify that evaluation with surprising precision.”

Castro predicts that Faceage could help doctors to better customize treatment plans or prioritize palliative care in oncology, “where resilience matters more than a date of birth.”

The doctor emphasized, however, that caution is key.

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“The AI ​​models are as good as the data in which they are trained,” Castro said. “If training data lacks diversity, we run the risk of producing biased results.”

“While Faceage can overcome doctors in some survival predictions, human judgment should increase, not to cancel it.”

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Castro also warned about possible ethical concerns.

“Who possesses facial data? How is it stored? Does patients understand what is being analyzed? These questions matter as much as technology itself,” he said.

There is also a psychological impact of the tool, Castro said.

“That they tell you that ‘you seem greater than your age could influence treatment decisions or self -perception in a way that we still do not even understand,” he said.

“We need a clear consent, data privacy and sensitivity. Nobody wants them to tell him that they seem older without context.”

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The conclusion, according to Castro, is that AI can improve a doctor’s trial, but cannot replace it.

“AI can improve our attention, but cannot replace empathy, context and humanity that define medicine.”