Implementation of Machine  Learning for Identification of  FamiHypercholesterolemia  Requires a “Human in the  Loop”: Lessons Learned from a  Novel Outreach Program in an  Academic Health System

doi:10.47739/vascularmedicine

Implementation of Machine Learning for Identification of FamiHypercholesterolemia Requires a “Human in the Loop”: Lessons Learned from a Novel Outreach Program in an Academic Health System - Abstract

The vast majority of individuals with heterozygous familial hypercholesterolemia (FH) remain undiagnosed despite a prevalence of approximately 1:250 – 1:300 in the general population [1-3]

Annals of Vascular Medicine and Research

Annals of Vascular Medicine and Research

Annals of Vascular Medicine and Research

Implementation of Machine Learning for Identification of FamiHypercholesterolemia Requires a “Human in the Loop”: Lessons Learned from a Novel Outreach Program in an Academic Health System - Abstract

JSciMed

Journals

Implementation of Machine Learning for Identification of FamiHypercholesterolemia Requires a “Human in the Loop”: Lessons Learned from a Novel Outreach Program in an Academic Health System - Abstract

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