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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.