The use of machine learning (ML) models have become a crucial factor in the growing field
of healthcare, ushering in a new era of medical research and diagnosis. This study …

With the rapid development of medicine and technology, machine learning (ML) techniques
are extensively applied to medical informatics and the suboptimal health field to identify …

Background and objectives Chronic kidney disease (CKD) is a global health concern. This
study aims to identify key factors associated with renal function changes using the proposed …

Vertical federated learning (VFL) has recently emerged as an appealing distributed
paradigm empowering multi-party collaboration for training high-quality models over …

Background Many individuals with hypertension remain undiagnosed. We aimed to develop
a predictive model for hypertension using diagnostic codes from prevailing electronic …

Lowing blood lipid levels with probiotics has good application prospects. This study aimed to
isolate probiotics with hypolipidemic efficacy from homemade na dish and investigate their …

Background This study aimed to predict early adolescent sleep problems using pregnancy
and childbirth risk factors through machine learning algorithms, and to evaluate model …

This study assessed the association between atherosclerosis indices, serum uric acid to
high‐density lipoprotein cholesterol ratio (UHR) and triglyceride‐glucose (TyG) index and …

Longitudinal data, while often limited, contain valuable insights into features impacting
clinical outcomes. To predict the progression of chronic kidney disease (CKD) in patients …

Purpose Dyslipidemia poses a significant risk for the progression to cardiovascular
diseases. Despite the identification of numerous risk factors and the proposal of various risk …