Metabolic abnormalities lead to the dysfunction of metabolic pathways and metabolite
accumulation or deficiency which is well-recognized hallmarks of diseases. Metabolite …

As an integral aspect of healthcare, digital technology has enabled modeling of complex
relationships to detect, screen, diagnose and predict patient outcomes. With massive …

Hypertension is the leading cause of cardiovascular complications. This review focuses on
the advancements in medical artificial intelligence (AI) models aimed at individualized …

Background Machine learning (ML) classifiers are increasingly used for predicting
cardiovascular disease (CVD) and related risk factors using omics data, although these …

Background This research aimed to develop a model for individualized treatment decision-
making in inoperable elderly patients with esophageal squamous cell carcinoma (ESCC) …

Background Machine learning (ML) integration of clinical, metabolite, and genetic data
reveals variable results in predicting cardiometabolic health (CMH) outcomes. Therefore, we …

Hypertension is an important modifiable risk factor for morbidity and mortality associated
with cardiovascular disease. The incidence of hypertension is increasing not only in Korea …

The single largest contributor to human mortality is cardiovascular disease, the top risk factor
for which is hypertension (HTN). The last two decades have placed much emphasis on the …

Complex multi-omics effects drive the clustering of cardiometabolic risk factors, underscoring
the imperative to comprehend how individual and combined omics shape phenotypic …

Hypertension is a major preventable risk factor for cardiovascular disease, affecting over 1.5
billion adults worldwide. Antihypertensive peptides (AHTPs) have gained attention as a …