BACKGROUND: The prediction of mortality for elderly patients undergoing non-cardiac surgeries is a vital research area, as accurate risk assessment can help surgeons make better clinical decisions during the perioperative period. This study aims to b...
BACKGROUND: Stress hyperglycemia ratio (SHR) and glycemic variability (GV) reflect acute glucose elevation and fluctuations, which correlate with adverse outcomes in patients with atherosclerotic cardiovascular disease (ASCVD). However, the prognosti...
BACKGROUND: Rapid technological advancements have left medical graduates potentially underprepared for the digital healthcare environment. Despite the importance of digital health education, consensus on essential primary medical degree content is la...
BACKGROUND: Vascular smooth muscle cells loaded with cholesterol (foam-VSMCs) play a crucial role in the progression of human atherosclerosis. Exchange Protein Directly Activated by cAMP 1 (EPAC1) is a critical protein in the regulation of vascular t...
BACKGROUND: Mobile health (mHealth) applications (apps) integrated with artificial intelligence for skin cancer triage are increasingly available to the general public. Nevertheless, their actual uptake is limited. Although endorsement by healthcare ...
BACKGROUND: The occurrence of short birth intervals among reproductive-age women in East Africa is a critical public health issue, contributing to maternal and child health risks. Identifying the key factors that predict short birth intervals can hel...
BACKGROUND: Suicide poses a substantial public health challenge globally, with the elderly population being particularly vulnerable. Research into suicide risk factors among elderly inpatients with non-psychiatric disorders remains limited. This inve...
BACKGROUND: Older patients with cardiovascular disease often experience frailty and sarcopenia. We evaluated whether a reduced blood flow in the splenic and portal vein is associated with frailty and sarcopenia in older patients with cardiovascular d...
The study aimed to develop a predictive model using machine learning algorithms, providing healthcare professionals with a novel tool for assessing disability risk in older adults. Data from the 2018 and 2020 waves of the China Health and Retirement ...
This study aims to predict hemorrhagic stroke outcomes, including 90-day prognosis and in-hospital mortality, using machine learning models and SHapley Additive exPlanations (SHAP) analysis. Data were collected from a national Stroke Registry from Ja...