The Many Faces of Genetic Illness Face recognition identifies childhood genetic diseases.

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Graphs showing how app Face2Gene works

People with certain genetic disorders share common facial features. Doctors are using computer vision to identify such syndromes in children so they can get early treatment.

What’s new: Face2Gene is an app from Boston-based FDNA that recognizes genetic disorders from images of patients’ faces. Introduced in 2014, it was upgraded recently to identify over 1,000 syndromes (more than three times as many as the previous version) based on fewer examples. In addition, the upgrade can recognize additional conditions as photos of them are added to the company’s database — no retraining required.

How it works: New work by Aviram Bar-Haim at FDNA, Tzung-Chien Hsieh at Rheinische Friedrich-Wilhelms-Universität Bonn, and colleagues describes the revised model.

  • Face2Gene’s underpinning is a convolutional neural network that was pretrained on 500,000 images of 10,000 faces and fine-tuned on proprietary data to classify 299 conditions such as Down syndrome and Noonan syndrome.
  • The developers removed the trained model’s classification layer to output a representation of each input face. They fed the model around 20,000 images labeled with 1,115 syndromes and stored their representations.
  • Presented with an unfamiliar face, the model calculates the cosine similarity between the new representation and those in the database.
  • It ranks the top 30 most similar representations. Their labels yield a ranked list of possible diagnoses.

Results: In tests, the new version proved somewhat less accurate than its predecessor at recognizing the 91 syndromes pictured in the London Medical Database. It ranked the correct syndrome in the top 30 possibilities 86.59 percent of the time versus the earlier version’s 88.34 percent. However, it was able to identify 816 conditions that its predecessor couldn’t, ranking the correct one in the top 30 possibilities 24.41 percent of the time and in the top position 7.07 percent of the time. (The chance of choosing the correct syndrome randomly was 0.09 percent.)

Why it matters: Some 350 million people worldwide live with a rare genetic disorder. Such conditions are especially difficult to diagnose because they’re so numerous, and many doctors never encounter a case. Face2Gene, which reportedly is used by thousands of geneticists, has been credited with making the job much easier.

We’re thinking: Humanity has a sad history of judging people based on appearance. While this model is designed for healthcare professionals to evaluate children who may need medical treatment, we caution against trying to use AI to classify an individual’s traits such as intelligence, character, or sexual preference based on their looks.

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