BACKGROUND: Preventive strategies integrated with digital health and artificial intelligence (AI) have significant potential to mitigate the global burden of atherosclerotic cardiovascular disease (ASCVD). AI-enabled clinical decision support (CDS) s...
Cardiovascular diseases (CVDs) are a major cause of morbidity and mortality worldwide. Effective CVD treatment requires early and accurate diagnosis. CVD diagnosis and prognosis can be done using medical image analysis. In this paper, we propose a no...
This systematic review aimed to evaluate the performance of machine learning (ML) models and conventional statistical models (CSMs) for predicting cardiovascular events in dialysis patients. Following PRISMA guidelines, eligible studies were searched...
BMC medical informatics and decision making
Nov 18, 2025
BACKGROUND: Cardiovascular disease (CVD) continues to be a leading cause of disease burden and mortality worldwide. Identifying reliable biomarkers for CVD risk assessment is essential. This study investigates the association between the C-reactive p...
Machine learning techniques earn higher accuracy and robustness in multimorbidity prediction at this moment in time. Among various forms of multimorbidity, complex multimorbidity, especially the intersection of cardiometabolic disorders and mental he...
Biomedical physics & engineering express
Nov 14, 2025
Electrocardiogram (ECG) and phonocardiogram (PCG) have emerged as crucial non-invasive and portable diagnostic modalities for early cardiovascular disease (CVD) screening. Despite the individual merits of these signal modalities in CVD detection, sig...
The rapid advancement of genomic and precision medicine has expanded the role of genetics and genomics in the diagnosis, risk stratification, and management of cardiovascular diseases. With the decreasing cost and increasing accessibility of genetic ...
BACKGROUND: Cardiovascular disease (CVD) remains a leading cause of preventable morbidity and mortality, highlighting the need for early risk stratification in primary prevention. Traditional Cox models assume proportional hazards and linear effects,...
The rapid development and integration of artificial intelligence (AI), including predictive, generative, and emerging agentic tools, into cardiovascular and stroke care is outpacing traditional evaluation frameworks and the generation of robust clini...
BACKGROUND: Cardiovascular diseases (CVD) are one of the leading global causes of death, which requires an accurate early prediction. This study aimed to develop transparent machine learning (ML) models using National Health and Nutrition Examination...
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