Machine learning for assessment of coronary artery disease in cardiac CT: a survey

N Hampe, JM Wolterink, SGM Van Velzen… - Frontiers in …, 2019 - frontiersin.org
Cardiac computed tomography (CT) allows rapid visualization of the heart and coronary
arteries with high spatial resolution. However, analysis of cardiac CT scans for manifestation …

A recurrent CNN for automatic detection and classification of coronary artery plaque and stenosis in coronary CT angiography

M Zreik, RW Van Hamersvelt… - IEEE transactions on …, 2018 - ieeexplore.ieee.org
Various types of atherosclerotic plaque and varying grades of stenosis could lead to different
management of patients with a coronary artery disease. Therefore, it is crucial to detect and …

Standardized evaluation framework for evaluating coronary artery stenosis detection, stenosis quantification and lumen segmentation algorithms in computed …

HA Kirişli, M Schaap, CT Metz, AS Dharampal… - Medical image …, 2013 - Elsevier
Though conventional coronary angiography (CCA) has been the standard of reference for
diagnosing coronary artery disease in the past decades, computed tomography …

Findings from machine learning in clinical medical imaging applications–Lessons for translation to the forensic setting

CA Peña-Solórzano, DW Albrecht, RB Bassed… - Forensic Science …, 2020 - Elsevier
Abstract Machine learning (ML) techniques are increasingly being used in clinical medical
imaging to automate distinct processing tasks. In post-mortem forensic radiology, the use of …

Automatic coronary artery plaque quantification and CAD-RADS prediction using mesh priors

RLM Van Herten, N Hampe, RAP Takx… - IEEE transactions on …, 2023 - ieeexplore.ieee.org
Coronary artery disease (CAD) remains the leading cause of death worldwide. Patients with
suspected CAD undergo coronary CT angiography (CCTA) to evaluate the risk of …

Automatic segmentation, detection and quantification of coronary artery stenoses on CTA

R Shahzad, H Kirişli, C Metz, H Tang, M Schaap… - The international journal …, 2013 - Springer
Accurate detection and quantification of coronary artery stenoses is an essential
requirement for treatment planning of patients with suspected coronary artery disease. We …

Current modeling methods used in QSAR/QSPR

LC Yee, YC Wei - … modelling of molecular descriptors in QSAR …, 2012 - Wiley Online Library
A drug company has to ensure the quality, safety, and efficacy of a marketed drug by
subjecting the drug to a variety of tests [1]. Therefore, drug development is a time-consuming …

Automatic coronary wall and atherosclerotic plaque segmentation from 3D coronary CT angiography

AM Ghanem, AH Hamimi, JR Matta, A Carass… - Scientific reports, 2019 - nature.com
Coronary plaque burden measured by coronary computerized tomography angiography
(CCTA), independent of stenosis, is a significant independent predictor of coronary heart …

[PDF][PDF] Automatic detection and characterization of coronary artery plaque and stenosis using a recurrent convolutional neural network in coronary CT angiography

M Zreik, RW van Hamersvelt, JM Wolterink… - arxiv. org, Cornell …, 2018 - researchgate.net
Different types of atherosclerotic plaque and varying grades of stenosis lead to different
management of patients with obstructive coronary artery disease. Therefore, it is crucial to …

A deep learning‐based interpretable decision tool for predicting high risk of chemotherapy‐induced nausea and vomiting in cancer patients prescribed highly …

J Zhang, X Cui, C Yang, D Zhong, Y Sun… - Cancer …, 2023 - Wiley Online Library
Objective This study aims to develop a risk prediction model for chemotherapy‐induced
nausea and vomiting (CINV) in cancer patients receiving highly emetogenic chemotherapy …