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Researchers at Yale School of Medicine have unveiled an artificial intelligence (AI) model that can accurately diagnose Marfan Syndrome using a facial photograph.
This genetic disorder affects 1 in 3,000 people and causes connective tissue issues that can lead to life-threatening conditions if left undiagnosed.
Characterized by distinct physical traits like tall stature, long faces, and joint issues, Marfan Syndrome can now be identified with 98.5% accuracy, enabling early intervention and improving patient outcomes.
🚨 👁AI breakthrough in rare disease diagnosis! 🧬 Yale researchers have developed an AI model that can identify Marfan syndrome from facial photos with 98.5% accuracy.
Someone say potential SUBNET on Bittensor!
• Early detection of this potentially fatal genetic condition
•… pic.twitter.com/lm6FJyyVKQ— Andy ττ (@bittingthembits) August 12, 2024
Marfan Syndrome often goes undiagnosed until severe complications, like aortic dissection, occur. The AI tool’s ability to identify individuals at risk from a simple photograph could revolutionize early diagnosis and treatment.
Notably, the pilot study conducted by the Yale team involved 672 facial photographs of individuals with and without Marfan Syndrome.
Researchers trained a Convolutional Neural Network (CNN) on 80% of these images and then tested its ability to distinguish between Marfan and non-Marfan faces in the remaining 20%.
The AI model achieved a 98.5% accuracy rate in identifying Marfan Syndrome.
The study’s senior author, Dr. John Elefteriades, a professor of surgery at Yale School of Medicine, emphasized the potential of this tool in enhancing diagnosis and enabling timely, protective treatments for patients at risk.
Dr. Elefteriades expressed optimism about the future applications of this technology, indicating plans to make the diagnostic tool available online. “We anticipate that many individuals may self-test once we put the test online,” he stated.
Historical Context of AI and Genetic Disorder Diagnosis
While AI in healthcare continues to gather momentum, this is not the first time AI will be used to diagnose genetic disorders.
In 2019, an AI-based program gained attention for its ability to suggest likely genetic disorders based on facial phenotypes. This program, which can be accessed via a smartphone app, requires nothing more than a photograph of the patient’s face and is widely used by geneticists globally.
The most prominent platform in this space, Face2Gene, developed by Boston-based FDNA, is utilized by 70% of the world’s geneticists across 2,000 clinical sites in 130 countries.
Face2Gene employs a facial image analysis framework called DeepGestalt, which uses computer vision and deep-learning algorithms to identify facial phenotypes of hundreds of diseases.
A facial recognition app called Face2Gene, developed by Boston-based digital health startup FDNA, is making diagnoses easier for specialists in genetic disorders. https://t.co/pSaWV5KiaD pic.twitter.com/yJhTPkJVT3
— The Boston Globe (@BostonGlobe) August 30, 2018
Similarly, in a study published in Nature Medicine, FDNA’s technology demonstrated a 91% accuracy rate in identifying the correct syndrome among various genetic disorders, outperforming expert clinicians in several experiments.
