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Researchers define new subtypes of common brain disorder
Artificial intelligence identified 3 subtypes of Chiari type-1 malformations, could improve medical decision making
Co-senior author David Limbrick, MD, PhD, now the James W. and Frances G. McGlothlin chair of the Department of Neurosurgery at Virginia Commonwealth University School of Medicine, approached Lu because the artificial intelligence tools like those with which he works are extremely good at sifting through large data sets to identify patterns and correlations within the many variables associated with Chiari type-1 cases. “With the growing power of computational tools and the vast data in electronic health records, AI can serve as a catalyst for generating novel insights for clinicians, enabling us to work together toward impactful discoveries and better patient care.” Gupta VP, Xu Z, Greenberg, JK, Strahle JM, Haller G, Meehan T, Roberts A, Limbrick Jr DD, Lu C. Using artificial intelligence to identify three presenting phenotypes of Chiari type-1 malformation and syringomyelia.
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