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Artificial intelligence can accelerate clinical diagnosis of fragile X syndrome


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Artificial intelligence can accelerate clinical diagnosis of fragile X syndrome
An analysis of electronic health records for 1.7 million Wisconsin patients revealed a variety of health problems newly associated with fragile X syndrome, the most common inherited cause of intellectual disability and autism, and may help identify cases years in advance of the typical clinical diagnosis.
Researchers from the Waisman Center at the University of Wisconsin-Madison found that people with fragile X are more likely than the general population to also have diagnoses for a variety of circulatory, digestive, metabolic, respiratory, and genital and urinary disorders. Their study, published recently in the journal Genetics in Medicine, the official journal of the American College of Medical Genetics and Genomics (ACMG), shows that machine learning algorithms may help identify undiagnosed cases of fragile X syndrome based on diagnoses of other physical and mental impairments ....

Marshfield Clinic , United States , University Of Wisconsin , Finn Kuusisto , Danielle Scholze , Jinkuk Hong , Ron Stewart , Arezoo Movaghar , Marsha Mailick , Leann Smith Dawalt , David Page Of Duke University , Waisman Center , Marshfield Clinic Health System , Morgridge Institute For Research , American College Of Medical Genetics , American College , Medical Genetics , David Page , Duke University , Morgridge Institute , மார்ஷ்ஃபீல்ட் சிகிச்சையகம் , ஒன்றுபட்டது மாநிலங்களில் , பல்கலைக்கழகம் ஆஃப் விஸ்கான்சின் , ரோன் ஸ்டீவர்ட் , வைஸ்மன் மையம் , மார்ஷ்ஃபீல்ட் சிகிச்சையகம் ஆரோக்கியம் அமைப்பு ,