Comparing a novel machine learning method to the Friedewald formula and Martin-Hopkins equation for low-density lipoprotein estimation

Comparing a novel machine learning method to the Friedewald formula and Martin-Hopkins equation for low-density lipoprotein estimation

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Background Low-density lipoprotein cholesterol (LDL-C) is a target for cardiovascular prevention. Contemporary equations for LDL-C estimation have limited accuracy in certain scenarios (high triglycerides [TG], very low LDL-C). Objectives We derived a novel method for LDL-C estimation from the stand...

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Bibliographic Details
Main Authors: Gurpreet Singh, Yasin Hussain, Zhuoran Xu, Evan Sholle, Kelly Michalak, Kristina Dolan, Benjamin C. Lee, Alexander R. van Rosendael, Zahra Fatima, Jessica M. Peña, Peter W. F. Wilson, Antonio M. Gotto, Leslee J. Shaw, Lohendran Baskaran, Subhi J. Al’Aref, Simeon-Pierre Choukem
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2020-01-01
Series:PLoS ONE
Online Access:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7526877/?tool=EBI

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https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7526877/?tool=EBI

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