Machine learning reveals genetic pathways in spina bifida, offering precision medicine hope

Spina bifida affects approximately 1,427 babies born annually in the United States, causing paralysis and high risk of complications when the neural tube fails to close during pregnancy.

At Weill Cornell Medicine, researchers have turned to machine learning to do what traditional science struggled to accomplish alone — find the hidden genetic architecture of spina bifida, a birth defect that quietly touches roughly 1,427 American families each year. By letting algorithms sort through genomic data without the guiding hand of human assumption, the team uncovered that glucose and lipid metabolism — the same pathways implicated in diabetes and obesity during pregnancy — appear central to the condition's origins. The finding, published in late 2021, is less a final answer than a ne

Machine learning reveals genetic pathways in spina bifida, offering precision medicine hope

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