If successfully introduced in medical community, this Artificial Intelligence (AI) called Face2Gene could help doctors find new treatments for rare diseases.
A new AI-powered by smartphone application called Face2Gene could change that medical struggles, because they can help them to identify rare disorders.
According to its creators say it can outperform doctors at diagnosing rare genetic disorders in children by analyzing kids’ faces.
Eventually, the app could help children across the globe receive better treatment for their conditions” if it can overcome a few hurdles.
The Face2Gene application is the work of Boston-based digital-health company FDNA, which describes its work in a study published in the journal “Nature Medicine”on Monday.
Citing the paper, the team trained Face2Gene’s deep-learning algorithm to identify rare genetic disorders by first feeding it more than 17,000 images of people diagnosed with one of 216 genetic syndromes.
Furthermore, from that data, it learned to look for distinctive facial features associated with specific disorders.
When the researchers tested the application on 502 images it hadn’t seen before, Face2Gene provided the correct diagnosis roughly 65 percent of the time.
When given the option of providing 10 possible diagnoses, the correct one made Face2Gene’s list 91 percent of the time.
The team also tested Face2Gene’s disorder-identification abilities against those of 49 clinical geneticists attending a workshop on birth defects.
For that unofficial trial, the researchers asked the participants to diagnose 10 children with fairly recognizable genetic syndromes based on a single photo of their face.
The results were striking. Only two of the clinical geneticists provided correct diagnoses for more than 50 percent of the photos. Face2Gene correctly diagnosed seven out of the 10 children.
Ideally, Face2Gene would be able to correctly identify a disorder every time. To get closer to that goal, the FDNA team needs more training data, which it hopes to generate by making the app available to healthcare professionals for free.
To further give reliable results, it also needs that training data to include more non-Caucasian faces.
Based on a 2017 study a using Face2Gene to identify Down Syndrome found the healthcare application was 80 accurate in its diagnosis if a photo featured a white Belgian child, but only 37 accurate if it featured a black Congolese child.