AIMC Topic: Coronary Artery Disease
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Ultralow dose coronary calcium scoring CT at reduced tube voltage and current by using deep learning image reconstruction.
European journal of radiology
Sep 19, 2024
OBJECTIVE: To explore the potential of the deep learning reconstruction (DLR) for ultralow dose calcium scoring CT (CSCT) with simultaneously reduced tube voltage and current.
Classification of coronary artery disease using radial artery pulse wave analysis via machine learning.
BMC medical informatics and decision making
Sep 16, 2024
BACKGROUND: Coronary artery disease (CAD) is a major global cardiovascular health threat and the leading cause of death in many countries. The disease has a significant impact in China, where it has become the leading cause of death. There is an urge...
Clinical impact of deep learning-derived intravascular ultrasound characteristics in patients with deferred coronary artery.
International journal of cardiology
Sep 13, 2024
Prognostic markers for long-term outcomes are lacking in patients with deferred (nonculprit) coronary artery lesions. This study aimed to identify the morphological criteria for predicting adverse outcomes and validate their clinical impact. Using de...
Artificial intelligence-assisted measurements of coronary computed tomography angiography parameters such as stenosis, flow reserve, and fat attenuation for predicting major adverse cardiac events in patients with coronary arterial disease.
Biomolecules & biomedicine
Sep 6, 2024
Advancements in artificial intelligence (AI) offer promising tools for improving diagnostic accuracy and patient outcomes in cardiovascular medicine. This study explores the potential of AI-assisted measurements in enhancing the prediction of major a...
Use machine learning models to identify and assess risk factors for coronary artery disease.
PloS one
Sep 6, 2024
Accurate prediction of coronary artery disease (CAD) is crucial for enabling early clinical diagnosis and tailoring personalized treatment options. This study attempts to construct a machine learning (ML) model for predicting CAD risk and further elu...
Long-term Major Adverse Cardiac Event Prediction by Computed Tomography-derived Plaque Measures and Clinical Parameters Using Machine Learning.
Internal medicine (Tokyo, Japan)
Sep 4, 2024
Objective The present study evaluated the usefulness of machine learning (ML) models with the coronary computed tomography imaging and clinical parameters for predicting major adverse cardiac events (MACEs). Methods The Nationwide Gender-specific Ath...
Fully automated epicardial adipose tissue volume quantification with deep learning and relationship with CAC score and micro/macrovascular complications in people living with type 2 diabetes: the multicenter EPIDIAB study.
Cardiovascular diabetology
Sep 3, 2024
BACKGROUND: The aim of this study (EPIDIAB) was to assess the relationship between epicardial adipose tissue (EAT) and the micro and macrovascular complications (MVC) of type 2 diabetes (T2D).
Humans
Prognosis
Female
Vascular Calcification
Computed Tomography Angiography
Adipose Tissue
Pericardium
Predictive Value of Tests
Epicardial Adipose Tissue
Middle Aged
Coronary Angiography
Risk Assessment
Radiographic Image Interpretation, Computer-Assisted
Coronary Artery Disease
Deep Learning
Adiposity
Diabetes Mellitus, Type 2
Reproducibility of Results
Automation
Risk Factors
Diabetic Angiopathies
Aged
Male
Can large language models be new supportive tools in coronary computed tomography angiography reporting?
Clinical imaging
Aug 31, 2024
The advent of large language models (LLMs) marks a transformative leap in natural language processing, offering unprecedented potential in radiology, particularly in enhancing the accuracy and efficiency of coronary artery disease (CAD) diagnosis. Wh...
A novel algorithm developed using machine learning and a J-ACCESS database can estimate defect scores from myocardial perfusion single-photon emission tomography images.
Annals of nuclear medicine
Aug 29, 2024
BACKGROUND: Stress myocardial perfusion single-photon emission computed tomography (SPECT) imaging (MPI) has been used to diagnose and predict the prognoses of patients with coronary artery disease (CAD). An ongoing multicenter collaboration establis...
Deep learning model for intravascular ultrasound image segmentation with temporal consistency.
The international journal of cardiovascular imaging
Aug 27, 2024
This study was conducted to develop and validate a deep learning model for delineating intravascular ultrasound (IVUS) images of coronary arteries.Using a total of 1240 40-MHz IVUS pullbacks with 191,407 frames, the model for lumen and external elast...
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