AI Medical Compendium Topic:
Coronary Artery Disease

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Machine learning-driven risk assessment of coronary heart disease: Analysis of NHANES data from 1999 to 2018.

Zhong nan da xue xue bao. Yi xue ban = Journal of Central South University. Medical sciences
OBJECTIVES: The high incidence of coronary artery heart disease (CHD) poses a significant burden and challenge to public health systems globally. Effective prevention and early diagnosis of CHD have become key strategies to alleviate this burden. Thi...

Prospective deep learning-based quantitative assessment of coronary plaque by computed tomography angiography compared with intravascular ultrasound: the REVEALPLAQUE study.

European heart journal. Cardiovascular Imaging
AIMS: Coronary computed tomography angiography provides non-invasive assessment of coronary stenosis severity and flow impairment. Automated artificial intelligence (AI) analysis may assist in precise quantification and characterization of coronary a...

Machine Learning Constructed Based on Patient Plaque and Clinical Features for Predicting Stent Malapposition: A Retrospective Study.

Clinical cardiology
BACKGROUND: Stent malapposition (SM) following percutaneous coronary intervention (PCI) for myocardial infarction continues to present significant clinical challenges. In recent years, machine learning (ML) models have demonstrated potential in disea...

Automated vessel-specific coronary artery calcification quantification with deep learning in a large multi-centre registry.

European heart journal. Cardiovascular Imaging
AIMS: Vessel-specific coronary artery calcification (CAC) is additive to global CAC for prognostic assessment. We assessed accuracy and prognostic implications of vessel-specific automated deep learning (DL) CAC analysis on electrocardiogram (ECG) ga...

Improved stent sharpness evaluation with super-resolution deep learning reconstruction in coronary CT angiography.

The British journal of radiology
OBJECTIVES: This study aimed to assess the impact of super-resolution deep learning reconstruction (SR-DLR) on coronary CT angiography (CCTA) image quality and blooming artifacts from coronary artery stents in comparison to conventional methods, incl...

Clinical named entity recognition for percutaneous coronary intervention surgical information with hybrid neural network.

The Review of scientific instruments
Percutaneous coronary intervention (PCI) has become a vital treatment approach for coronary artery disease, but the clinical data of PCI cannot be directly utilized due to its unstructured characteristics. The existing clinical named entity recogniti...

Artificial intelligence-based assessment of built environment from Google Street View and coronary artery disease prevalence.

European heart journal
BACKGROUND AND AIMS: Built environment plays an important role in the development of cardiovascular disease. Tools to evaluate the built environment using machine vision and informatic approaches have been limited. This study aimed to investigate the...

Artificial intelligence in Medicare: utilization, spending, and access to AI-enabled clinical software.

The American journal of managed care
OBJECTIVES: In 2018, CMS established reimbursement for the first Medicare-covered artificial intelligence (AI)-enabled clinical software: CT fractional flow reserve (FFRCT) to assist in the diagnosis of coronary artery disease. This study quantified ...

Prognostic value of a novel artificial intelligence-based coronary computed tomography angiography-derived ischaemia algorithm for patients with suspected coronary artery disease.

European heart journal. Cardiovascular Imaging
AIMS: Coronary computed tomography angiography (CTA) imaging is used to diagnose patients with suspected coronary artery disease (CAD). A novel artificial intelligence-guided quantitative computed tomography ischaemia algorithm (AI-QCTischaemia) aims...