Cardiovascular diseases (CVDs) are complex, multifactorial conditions that require personalized assessment and treatment. Advancements in multi-omics technologies, namely RNA sequencing and whole-genome sequencing, have provided translational researc...
Journal of atherosclerosis and thrombosis
Oct 30, 2024
AIMS: Artificial intelligence is increasingly used in the medical field. We assessed the accuracy and reproducibility of responses by ChatGPT to clinical questions (CQs) in the Japan Atherosclerosis Society Guidelines for Prevention Atherosclerotic C...
PURPOSE OF REVIEW: This opinion paper highlights the advancements in artificial intelligence (AI) technology for cardiovascular disease (CVD), presents best practices and transformative impacts, and addresses current concerns that must be resolved fo...
Ecotoxicology and environmental safety
Oct 23, 2024
BACKGROUND: Cardiovascular disease (CVD) remains a leading cause of mortality globally. Environmental pollutants, specifically volatile organic compounds (VOCs), have been identified as significant risk factors. This study aims to develop a machine l...
INTRODUCTION AND OBJECTIVES: Sri Lankans do not have a specific cardiovascular (CV) risk prediction model and therefore, World Health Organization(WHO) risk charts developed for the Southeast Asia Region are being used. We aimed to develop a CV risk ...
Computer methods and programs in biomedicine
Oct 19, 2024
BACKGROUND AND OBJECTIVE: Phonocardiogram (PCG) signal analysis is a non-invasive and cost-efficient approach for diagnosing cardiovascular diseases. Existing PCG-based approaches employ signal processing and machine learning (ML) for automatic disea...
Traditionally, machine learning-based clinical prediction models have been trained and evaluated on patient data from a single source, such as a hospital. Cross-validation methods can be used to estimate the accuracy of such models on new patients or...
BACKGROUND: Studies of cardiovascular disease risk prediction by machine learning algorithms often do not assess their ability to generalize to other populations and few of them include an analysis of the interpretability of individual predictions. T...
Computer methods and programs in biomedicine
Oct 9, 2024
BACKGROUND AND OBJECTIVE: Electrocardiogram (ECG) is one of the most important diagnostic tools for cardiovascular diseases (CVDs). Recent studies show that deep learning models can be trained using labeled ECGs to achieve automatic detection of CVDs...
BACKGROUND: Biological ageing markers are useful to risk stratify morbidity and mortality more precisely than chronological age. In this study, we aimed to develop a novel deep-learning-based biological ageing marker (referred to as RetiPhenoAge here...
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