AIMC Topic: Coronary Angiography
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First comparison between artificial intelligence-guided coronary computed tomography angiography versus single-photon emission computed tomography testing for ischemia in clinical practice.
Coronary artery disease
Dec 20, 2024
BACKGROUND: Noninvasive cardiac testing with coronary computed tomography angiography (CCTA) and single-photon emission computed tomography (SPECT) are becoming alternatives to invasive angiography for the evaluation of obstructive coronary artery di...
Artificial intelligence-derived coronary artery calcium scoring saves time and achieves close to radiologist-level accuracy accuracy on routine ECG-gated CT.
The international journal of cardiovascular imaging
Dec 16, 2024
Artificial Intelligence (AI) has been proposed to improve workflow for coronary artery calcium scoring (CACS), but simultaneous demonstration of improved efficiency, accuracy, and clinical stability have not been demonstrated. 148 sequential patients...
Multidetector Computed Tomography
Vascular Calcification
Computed Tomography Angiography
Cardiac-Gated Imaging Techniques
Retrospective Studies
Coronary Artery Disease
Female
Electrocardiography
Workflow
Reproducibility of Results
Humans
Observer Variation
Predictive Value of Tests
Male
Aged
Coronary Vessels
Artificial Intelligence
Coronary Angiography
Middle Aged
Radiologists
Severity of Illness Index
Radiographic Image Interpretation, Computer-Assisted
Time Factors
Machine learning-based radiomic features of perivascular adipose tissue in coronary computed tomography angiography predicting inflammation status around atherosclerotic plaque: a retrospective cohort study.
Annals of medicine
Dec 12, 2024
OBJECTIVES: This study expolored the relationship between perivascular adipose tissue (PVAT) radiomic features derived from coronary computed tomography angiography (CCTA) and the presence of coronary artery plaques. It aimed to determine whether PVA...
Artificial Intelligence-Driven Assessment of Coronary Computed Tomography Angiography for Intermediate Stenosis: Comparison With Quantitative Coronary Angiography and Fractional Flow Reserve.
The American journal of cardiology
Dec 11, 2024
We aimed to compare artificial intelligence (AI)-based coronary stenosis evaluation of coronary computed tomography angiography (CCTA) with its quantitative counterpart of invasive coronary angiography (ICA) and invasive fractional flow reserve (FFR)...
AI-CADR: Artificial Intelligence Based Risk Stratification of Coronary Artery Disease Using Novel Non-Invasive Biomarkers.
IEEE journal of biomedical and health informatics
Dec 5, 2024
Coronary artery disease (CAD) is one of the most common causes of sudden cardiac arrest, accounting for a large percentage of global mortality. A timely diagnosis and detection may save a person's life. The research suggests a methodological framewor...
Diagnostic Performance of Artificial Intelligence-Based Angiography-Derived Non-Hyperemic Pressure Ratio Using Pressure Wire as Reference.
Circulation journal : official journal of the Japanese Circulation Society
Dec 4, 2024
BACKGROUND: The angiography-derived non-hyperemic pressure ratio (angioNHPR) is a novel index of NHPR based on artificial intelligence (AI) that does not require pressure wires. We investigated the diagnostic accuracy of angioNHPR for detecting hemod...
Cohort profile: AI-driven national Platform for CCTA for clinicaL and industriaL applicatiOns (APOLLO).
BMJ open
Dec 2, 2024
PURPOSE: Coronary CT angiography (CCTA) is well established for the diagnostic evaluation and prognostication of coronary artery disease (CAD). The growing burden of CAD in Asia and the emergence of novel CT-based risk markers highlight the need for ...
Constraint-Aware Learning for Fractional Flow Reserve Pullback Curve Estimation From Invasive Coronary Imaging.
IEEE transactions on medical imaging
Dec 2, 2024
Estimation of the fractional flow reserve (FFR) pullback curve from invasive coronary imaging is important for the intraoperative guidance of coronary intervention. Machine/deep learning has been proven effective in FFR pullback curve estimation. How...
Assessing the need for coronary angiography in high-risk non-ST-elevation acute coronary syndrome patients using artificial intelligence and computed tomography.
The international journal of cardiovascular imaging
Nov 8, 2024
PURPOSE: This study aimed to evaluate the efficacy of the Chat Generative Pre-trained Transformer (ChatGPT) in guiding the need for invasive coronary angiography (ICA) in high-risk non-ST-elevation (NSTE) acute coronary syndrome (ACS) patients based ...
Acute Coronary Syndrome
Aged
Clinical Decision-Making
Humans
Double-Blind Method
Female
Computed Tomography Angiography
Male
Artificial Intelligence
Reproducibility of Results
Coronary Angiography
Non-ST Elevated Myocardial Infarction
Middle Aged
Decision Support Techniques
Risk Factors
Radiographic Image Interpretation, Computer-Assisted
Predictive Value of Tests
Prospective Studies
Risk Assessment
Predictive performance of machine learning models for kidney complications following coronary interventions: a systematic review and meta-analysis.
International urology and nephrology
Oct 31, 2024
BACKGROUND: Acute kidney injury (AKI) and contrast-induced nephropathy (CIN) are common complications following percutaneous coronary intervention (PCI) or coronary angiography (CAG), presenting significant clinical challenges. Machine learning (ML) ...
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