AIMC Topic: Coronary Artery Disease

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Predicting the future risk and outcomes of severe heart failure and coronary artery disease with machine learning in the UK Biobank Cohort.

PloS one
BACKGROUND: In order to seriously impact the global burden of heart failure (HF) and coronary artery disease (CAD), identifying at-risk individuals as early as possible is vital. Risk calculator tools in wide clinical use today are informed by tradit...

VO Max in Clinical Cardiology: Clinical Applications, Evidence Gaps, and Future Directions.

Current cardiology reports
PURPOSE OF REVIEW: VO₂ max is a fundamental marker of cardiorespiratory fitness with substantial prognostic and diagnostic value within the field of cardiology. This review analyzes current and emerging evidence regarding its clinical uses, highlight...

Machine learning-based CAD detection using integrated ECG and PCG parameter features.

Biomedical physics & engineering express
The combined analysis of electrocardiogram (ECG) and phonocardiogram signals(PCG) has demonstrated significant potential in the non-invasive detection of coronary artery disease (CAD). The efficacy of combining cardiac pathological parameters such as...

Pulse wave-driven machine learning for the non-invasive assessment of coronary artery calcification in patients with end-stage renal disease undergoing hemodialysis.

Biomedical engineering online
BACKGROUND: Coronary artery calcification (CAC) represents a major cardiovascular risk in patients with end-stage renal disease (ESRD) undergoing hemodialysis. Given that radial artery pulse waveforms can reflect vascular status, this study aimed to ...

Machine learning in predicting preoperative intra-aortic balloon pump use in patients undergoing coronary artery bypass grafting.

Journal of cardiothoracic surgery
BACKGROUND: Intra-aortic balloon pump (IABP) implantation in the perioperative period of cardiac surgery is an auxiliary treatment for cardiogenic shock. However, there is a lack of effective prediction models for preoperative IABP implantation.

A heart failure classification model from radial artery pulse wave using LSTM neural networks.

BMC medical informatics and decision making
BACKGROUND: Heart failure (HF) represents a pressing global health issue demanding innovative and accessible approaches for early detection. Non-invasive, rapid, and cost-effective techniques utilizing deep learning (DL) hold significant promise for ...

Immunophenotyping identifies key immune biomarkers for coronary artery disease through machine learning.

PloS one
INTRODUCTION: The differences among immune subtypes in coronary artery disease (CAD), their interrelationships, and the associated immune biomarkers remain incompletely understood.

The role of artificial intelligence in early detection and intervention of coronary artery disease.

Current opinion in cardiology
PURPOSE OF REVIEW: The diagnosis and management of coronary artery disease (CAD) involves complex delivery of care. Artificial intelligence (AI) proves to be a timely solution to challenges with diagnostics and timely and appropriate, quality of care...