Biomedical physics & engineering express
Oct 23, 2025
Cardiovascular disease (CVD) is a major cause of morbidity and mortality in diabetic populations. Early detection of cardiovascular risk in diabetes is crucial to reduce complications, particularly in resource-limited settings. This study aimed to de...
OBJECTIVE: This study investigated the relationship between estimated glucose disposal rate (eGDR), aging acceleration (AgeAccel), and mortality in adults diagnosed with cardiovascular-kidney-metabolic (CKM) stages 1 to 4.
BACKGROUND: Epicardial adipose tissue is gaining increasing interest as a cardiometabolic imaging biomarker, but its exact role in coronary artery disease is not fully understood. This study aimed to investigate the relationship between epicardial ad...
BACKGROUND: Diabetic nephropathy (DN), a severe complication of diabetes, is characterized by proteinuria, hypertension, and progressive renal function decline, potentially leading to end-stage renal disease. The International Diabetes Federation pro...
Generating appropriate ecological risk assessments to support the rapid growth of nanotechnology requires a comprehensive understanding of the potential effects of engineered nanomaterials (ENMs), both toxic and beneficial, and accurate predictions o...
Violence risk assessment is a critical component of psychiatric practice, with significant clinical, ethical, and legal implications. Psychiatric patients at high risk of violence often face interventions including restraints, intramuscular injection...
Cardiovascular diseases (CVDs) are the leading cause of death worldwide, and current predictors such as lipoprotein (a) [Lp(a)] and risk scores have limitations. Automated machine learning (AutoML) offers the potential to improve CVD risk prediction ...
BACKGROUND: It remains unclear whether certain individuals with type 2 diabetes (T2D) derive greater cardiovascular benefit from GLP-1 receptor agonists (GLP-1RAs). Here, we integrate individual-level data from cardiovascular outcome trials (CVOTs) a...
BACKGROUND: Rising osteoporosis prevalence among elderly populations and limitations of current single-factor screening methods necessitate development of comprehensive multi-dimensional risk prediction models.
BACKGROUND: Machine learning (ML) models have shown good performance in predicting cardiovascular disease risk. However, the usefulness of ML models has yet to be fully elucidated for sudden cardiac death (SCD) risk using long-term follow-up electron...
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