Finding missed cases of familial hypercholesterolemia in health systems using machine learning

Volume: 2, Issue: 1
Published: Apr 11, 2019
Abstract
Familial hypercholesterolemia (FH) is an underdiagnosed dominant genetic condition affecting approximately 0.4% of the population and has up to a 20-fold increased risk of coronary artery disease if untreated. Simple screening strategies have false positive rates greater than 95%. As part of the FH Foundation′s FIND FH initiative, we developed a classifier to identify potential FH patients using electronic health record (EHR) data at Stanford...
Paper Details
Title
Finding missed cases of familial hypercholesterolemia in health systems using machine learning
Published Date
Apr 11, 2019
Volume
2
Issue
1
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