AIMC Topic: Cardiovascular Diseases
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Gender-specific aspects of socialisation and risk of cardiovascular disease among community-dwelling older adults: a prospective cohort study using machine learning algorithms and a conventional method.
Journal of epidemiology and community health
Nov 11, 2024
BACKGROUND: Gender influences cardiovascular disease (CVD) through norms, social relations, roles and behaviours. This study identified gender-specific aspects of socialisation associated with CVD.
Carcinogenic and non-carcinogenic risks caused by rice contamination with heavy metals and their effect on the prevalence of cardiovascular disease (Using machine learning).
Food and chemical toxicology : an international journal published for the British Industrial Biological Research Association
Nov 7, 2024
INTRODUCTION: The safety and health of food products are essential in the food industry, and the risk of contamination from various contaminants must be evaluated. Exposure to HMs from the environment (especially food) causes various adverse effects ...
FMI-CAECD: Fusing Multi-Input Convolutional Features with Enhanced Channel Attention for Cardiovascular Diseases Prediction.
Sensors (Basel, Switzerland)
Nov 7, 2024
Cardiovascular diseases (CVD) have become a major public health problem affecting the national economy and social development, and have become one of the major causes of death. Therefore, the prevention, control and risk assessment of CVD have been i...
Artificial intelligence-based prediction of neurocardiovascular risk score from retinal swept-source optical coherence tomography-angiography.
Scientific reports
Nov 7, 2024
The recent rise of artificial intelligence represents a revolutionary way of improving current medical practices, including cardiovascular (CV) assessment scores. Retinal vascular alterations may reflect systemic processes such as the presence of CV ...
Development and Validation of a Predictive Model for Maternal Cardiovascular Morbidity Events in Patients With Hypertensive Disorders of Pregnancy.
Anesthesia and analgesia
Nov 6, 2024
BACKGROUND: Hypertensive disorders of pregnancy (HDP) are a major contributor to maternal morbidity, mortality, and accelerated cardiovascular (CV) disease. Comorbid conditions are likely important predictors of CV risk in pregnant people. Currently,...
Multimodal AI/ML for discovering novel biomarkers and predicting disease using multi-omics profiles of patients with cardiovascular diseases.
Scientific reports
Nov 3, 2024
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...
ChatGPT Responses to Clinical Questions in the Japan Atherosclerosis Society Guidelines for Prevention of Atherosclerotic Cardiovascular Disease 2022.
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...
Artificial Intelligence Algorithms in Cardiovascular Medicine: An Attainable Promise to Improve Patient Outcomes or an Inaccessible Investment?
Current cardiology reports
Oct 29, 2024
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...
Identifying cardiovascular disease risk in the U.S. population using environmental volatile organic compounds exposure: A machine learning predictive model based on the SHAP methodology.
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...
Development and validation of a cardiovascular risk prediction model for Sri Lankans using machine learning.
PloS one
Oct 22, 2024
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 ...
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