A comprehensive evaluation of LGMM’s performance across different scenarios.

A comprehensive evaluation of LGMM’s performance across different scenarios.

<p>Panel (a) shows the aggregate performance metrics of LGMM and LR models, highlighting the comparative performance based on the averaged values across three visits. Panel (b) details LGMM’s performance per visit.</p>

محفوظ في:

التفاصيل البيبلوغرافية
المؤلف الرئيسي:	Duy Nguyen (1831585) (author)
مؤلفون آخرون:	Ca Hoang (21722158) (author), Tien Truong (21722161) (author), Dang Nguyen (3506192) (author), Hillary Gia Lam (21722164) (author), Abhay Sharma (105087) (author), Trung Quoc Le (21722167) (author), Phat Kim Huynh (21722170) (author)
منشور في:	2025
الموضوعات:	Medicine Pharmacology Biotechnology Sociology Biological Sciences not elsewhere classified Mathematical Sciences not elsewhere classified three advanced steps relationships &# 160 profound &# 160 predictive modeling due offering robust tools maces ), attributed enabling detailed tracking classify patient data predicting cvd outcomes cvd &# 160 longitudinal perspective necessary level phenotypic models identify longitudinal transitions gaussian mixture models wisconsin sleep cohort unique risk profiles level phenotypic model high diagnostic accuracy presenting significant challenges predicting cvd onset distinct phenotypic clusters disease progression pathways cvd onset longitudinal cohort based models higher risk effects model cardiovascular disease aggregate accuracy significant roles significant factors total cholesterol top predictors sympathetic activation study utilizes study provides study addresses several decades progression rates predominant role methodology consists marked differences logistic mixed individual trajectories feature importance diabetes emerged density lipoprotein complex interplay comorbid conditions clinical indicators
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