BACKGROUND: The glucose disposal rate (eGDR) and a body shape index (ABSI) are predictors strongly associated with cardiovascular disease (CVD) and outcomes. However, whether they have additive effects on CVD risk is unknown. This study aimed to inve...
BMC medical informatics and decision making
Aug 11, 2025
The integration of electronic medical records (EMRs) with artificial intelligence (AI) is enhancing medical research, particularly in real-world evidence (RWE) studies. Extracting insights from coded medical data, such as ICD-10 codes, is essential f...
BACKGROUND: Atherosclerotic cardiovascular disease poses a heavy burden on the population's health and health care costs. Identifying apparently healthy individuals at risk of developing cardiovascular diseases using clinical prediction models raises...
The rapid development of digital therapeutics (DTx) presents opportunities for cardiovascular diseases (CVD) intervention. This review aims to summarize the technologies and applications of DTx in the field of cardiovascular healthcare. It seeks to i...
Statins are widely prescribed for the primary prevention of cardiovascular diseases, yet individual responses vary, necessitating personalized treatment strategies. Conventional approaches prioritize treating high-risk patients, but advancements in m...
BACKGROUND: Cardiovascular disease (CVD) is the leading cause of mortality and morbidity in China and worldwide while we are lacking in validated primary prevention model specifically for Chinese. To identify CVD high-risk individuals for early inter...
Cardiovascular illnesses continue to be a predominant cause of mortality globally, underscoring the necessity for prompt and precise diagnosis to mitigate consequences and healthcare expenditures. This work presents a complete hybrid methodology that...
In the healthcare industry, the Semantic Web offers to manage a huge amount of medical data which is machine-readable and machine-understandable as well. This domain incorporates ontologies, linked data, and semantic web technologies to promote healt...
Understanding how risk factors interact to jointly influence disease risk can provide insights into disease development and improve risk prediction. Here we introduce survivalFM, a machine learning extension to the widely used Cox proportional hazard...
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