AI Medical Compendium Topic

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Cardiovascular Diseases

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Predictive analytics for cardiovascular patient readmission and mortality: An explainable approach.

Computers in biology and medicine
BACKGROUND: Cardiovascular patients experience high rates of adverse outcomes following discharge from hospital, which may be preventable through early identification and targeted action. This study aimed to investigate the effectiveness and explaina...

Deep learning of movement behavior profiles and their association with markers of cardiometabolic health.

BMC medical informatics and decision making
BACKGROUND: Traditionally, existing studies assessing the health associations of accelerometer-measured movement behaviors have been performed with few averaged values, mainly representing the duration of physical activities and sedentary behaviors. ...

Artificial intelligence in preventive cardiology.

Progress in cardiovascular diseases
Artificial intelligence (AI) is a field of study that strives to replicate aspects of human intelligence into machines. Preventive cardiology, a subspeciality of cardiovascular (CV) medicine, aims to target and mitigate known risk factors for CV dise...

BREATH-Net: a novel deep learning framework for NO prediction using bi-directional encoder with transformer.

Environmental monitoring and assessment
Air pollution poses a significant challenge in numerous urban regions, negatively affecting human well-being. Nitrogen dioxide (NO) is a prevalent atmospheric pollutant that can potentially exacerbate respiratory ailments and cardiovascular disorders...

Transforming the cardiometabolic disease landscape: Multimodal AI-powered approaches in prevention and management.

Cell metabolism
The rise of artificial intelligence (AI) has revolutionized various scientific fields, particularly in medicine, where it has enabled the modeling of complex relationships from massive datasets. Initially, AI algorithms focused on improved interpreta...

hART: Deep learning-informed lifespan heart failure risk trajectories.

International journal of medical informatics
BACKGROUND: Heart failure (HF) results in persistent risk and long-term comorbidities. This is particularly true for patients with lifelong HF sequelae of cardiovascular disease such as patients with congenital heart disease (CHD).

Implications of Bias in Artificial Intelligence: Considerations for Cardiovascular Imaging.

Current atherosclerosis reports
PURPOSE OF REVIEW: Bias in artificial intelligence (AI) models can result in unintended consequences. In cardiovascular imaging, biased AI models used in clinical practice can negatively affect patient outcomes. Biased AI models result from decisions...

Improving deep-learning electrocardiogram classification with an effective coloring method.

Artificial intelligence in medicine
Cardiovascular diseases, particularly arrhythmias, remain a leading cause of mortality worldwide. Electrocardiogram (ECG) analysis plays a pivotal role in cardiovascular disease diagnosis. Although previous studies have focused on waveform analysis a...

Prediction of certainty in artificial intelligence-enabled electrocardiography.

Journal of electrocardiology
BACKGROUND: The 12‑lead ECG provides an excellent substrate for artificial intelligence (AI) enabled prediction of various cardiovascular diseases. However, a measure of prediction certainty is lacking.

Artificial intelligence in the risk prediction models of cardiovascular disease and development of an independent validation screening tool: a systematic review.

BMC medicine
BACKGROUND: A comprehensive overview of artificial intelligence (AI) for cardiovascular disease (CVD) prediction and a screening tool of AI models (AI-Ms) for independent external validation are lacking. This systematic review aims to identify, descr...