XGBOOST MACHINE LEARNING TO IDENTIFY PREDICTIVE VALUES OF CARDIOMETABOLIC RISK FOR COGNITIVE DECLINE AND MORTALITY

Abstract

Aim: To investigate the crucial biomarkers of cardiometabolic disorders that contribute to the risk of cognitive decline and mortality among adults with cognitive decline and dementia. Methods: We analyzed a cohort of 6814 participants aged 45 to 84 years at the baseline of 2000-2002 in the Multi-Ethnic Study of Atherosclerosis.

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