AIMC Topic: Coronary Artery Disease

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[Automated Classification of Calcification and Stent on Computed Tomography Coronary Angiography Using Deep Learning].

Nihon Hoshasen Gijutsu Gakkai zasshi
In computed tomography coronary angiography (CTCA), calcification and stent make it difficult to evaluate intravascular lumen. This is a cause of low positive-predictive value of coronary stenosis. Therefore, it is expected to develop a computer-aide...

Plasma fatty acid profile as biomarker of coronary artery disease: a pilot study using fourth generation artificial neural networks.

Journal of biological regulators and homeostatic agents
Many studies, focused on identifying new biomarkers for coronary artery disease (CAD) risk computation and monitoring, suggested a potential diagnostic role for fatty acids (FA). In the present study, we explored the potential diagnostic role of FA b...

[Comparison of outcomes of two minimally invasive approaches for multi-vessel coronary revascularization].

Beijing da xue xue bao. Yi xue ban = Journal of Peking University. Health sciences
OBJECTIVE: To compare the safety and effectiveness of two minimally invasive approaches for multi-vessel coronary revascularization.

Percutaneous coronary intervention using a combination of robotics and telecommunications by an operator in a separate physical location from the patient: an early exploration into the feasibility of telestenting (the REMOTE-PCI study).

EuroIntervention : journal of EuroPCR in collaboration with the Working Group on Interventional Cardiology of the European Society of Cardiology
AIMS: The present study explores the feasibility of telestenting, wherein a physician operator performs stenting on a patient in a separate physical location using a combination of robotics and telecommunications.

Evaluation of Machine Learning Methods to Predict Coronary Artery Disease Using Metabolomic Data.

Studies in health technology and informatics
Metabolomic data can potentially enable accurate, non-invasive and low-cost prediction of coronary artery disease. Regression-based analytical approaches however might fail to fully account for interactions between metabolites, rely on a priori selec...

Vessel extraction in X-ray angiograms using deep learning.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Coronary artery disease (CAD) is the most common type of heart disease which is the leading cause of death all over the world. X-ray angiography is currently the gold standard imaging technique for CAD diagnosis. These images usually suffer from low ...

Bailouts to LIMA Damage for Avoiding Conversion in Minimal Access Coronary Procedures.

The Annals of thoracic surgery
Minimally invasive and robotic coronary revascularization strategies offer less pain, fewer adverse events, better cosmesis, and speedier recovery. These procedures are vulnerable to left internal mammary artery (LIMA) injury that may require a full ...

Length of Hospital Stay Prediction at the Admission Stage for Cardiology Patients Using Artificial Neural Network.

Journal of healthcare engineering
For hospitals' admission management, the ability to predict length of stay (LOS) as early as in the preadmission stage might be helpful to monitor the quality of inpatient care. This study is to develop artificial neural network (ANN) models to predi...