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Carotid Stenosis

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PSAA-nnUNet: An Efficient Method for CT Carotid Artery Image Segmentation.

Advances in experimental medicine and biology 39400833
Carotid artery (CA) stenosis (CAS) constitutes a significant factor to ischaemic cerebrovascular events which exhibiting no overt symptoms in the early stages. Early detection of CAS can prevent ischaemic stroke and improve patient prognosis. In this...
Algorithms Carotid Arteries Carotid Stenosis Computed Tomography Angiography Deep Learning Humans Neural Networks, Computer Radiographic Image Interpretation, Computer-Assisted Tomography, X-Ray Computed
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Classification of Carotid Plaque with Jellyfish Sign Through Convolutional and Recurrent Neural Networks Utilizing Plaque Surface Edges.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference 40040199
In carotid arteries, plaque can develop as localized elevated lesions. The Jellyfish sign, marked by fluctuating plaque surfaces with blood flow pulsation, is a dynamic characteristic of these plaques that has recently attracted attention. Detecting ...
Algorithms Carotid Arteries Carotid Stenosis Deep Learning Humans Image Processing, Computer-Assisted Neural Networks, Computer Plaque, Atherosclerotic Recurrent Neural Networks Ultrasonography
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[Deep Learning-Based Artificial Intelligence Model for Automatic Carotid Plaque Identification].

Zhongguo yi liao qi xie za zhi = Chinese journal of medical instrumentation 39155246
This study aims at developing a dataset for determining the presence of carotid artery plaques in ultrasound images, composed of 1761 ultrasound images from 1165 participants. A deep learning architecture that combines bilinear convolutional neural n...
Artificial Intelligence Carotid Arteries Carotid Artery Diseases Carotid Stenosis Deep Learning Humans Image Processing, Computer-Assisted Neural Networks, Computer Plaque, Atherosclerotic Ultrasonography
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Using Machine Learning to Predict Outcomes Following Transfemoral Carotid Artery Stenting.

Journal of the American Heart Association 39189482
BACKGROUND: Transfemoral carotid artery stenting (TFCAS) carries important perioperative risks. Outcome prediction tools may help guide clinical decision-making but remain limited. We developed machine learning algorithms that predict 1-year stroke o...
Aged Aged, 80 and over Carotid Stenosis Databases, Factual Endovascular Procedures Female Femoral Artery Humans Machine Learning Male Middle Aged Predictive Value of Tests Retrospective Studies Risk Assessment Risk Factors Stents Stroke Time Factors Treatment Outcome
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Determination of spectroscopy marker of atherosclerotic carotid stenosis using FTIR-ATR combined with machine learning and chemometrics analyses.

Nanomedicine : nanotechnology, biology, and medicine 39341479
Atherosclerotic carotid stenosis (ACS) is a recognized risk factor for ischemic stroke. Currently, the gold diagnostic standard is Doppler ultrasound, the results of which do not provide certainty whether a given person should be qualified for surger...
Aged Atherosclerosis Biomarkers Carotid Stenosis Female Humans Machine Learning Male Middle Aged Principal Component Analysis Spectroscopy, Fourier Transform Infrared
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Raman spectroscopy combined with machine learning and chemometrics analyses as a tool for identification atherosclerotic carotid stenosis from serum.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy 39340949
Atherosclerosis carotid stenosis (ACS) is one of the main causes of stroke. Unfortunately, the highest number of people go to the doctor with an advanced disease or as a result of a stroke, because carotid atherosclerosis does not cause obvious sympt...
Aged Algorithms Carotid Stenosis Female Humans Machine Learning Male Middle Aged Principal Component Analysis ROC Curve Spectrum Analysis, Raman
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Advancing Vascular Surgery: The Role Of Artificial Intelligence And Machine Learning In Managing Carotid Stenosis.

Portuguese journal of cardiac thoracic and vascular surgery 39820882
INTRODUCTION: Cardiovascular diseases affect 17.7 million people annually, worldwide. Carotid degenerative disease, commonly described as atherosclerotic plaque accumulation, significantly contributes to this, posing a risk for cerebrovascular events...
Artificial Intelligence Carotid Stenosis Endarterectomy, Carotid Humans Machine Learning Risk Assessment
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Predictive Factors Driving Positive Awake Test in Carotid Endarterectomy Using Machine Learning.

Annals of vascular surgery 39580028
BACKGROUND: Positive neurologic awake testing during the carotid cross-clamping may be present in around 8% of patients undergoing carotid endarterectomy (CEA). The present work aimed to assess the accuracy of an artificial intelligence (AI)-powered ...
Aged Aged, 80 and over Carotid Stenosis Case-Control Studies Decision Support Techniques Endarterectomy, Carotid Female Humans Intraoperative Neurophysiological Monitoring Machine Learning Male Middle Aged Neurologic Examination Predictive Value of Tests Reproducibility of Results Retrospective Studies Risk Assessment Risk Factors Treatment Outcome Wakefulness
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Varying pixel resolution significantly improves deep learning-based carotid plaque histology segmentation.

Scientific reports 39747244
Carotid plaques-the buildup of cholesterol, calcium, cellular debris, and fibrous tissues in carotid arteries-can rupture, release microemboli into the cerebral vasculature and cause strokes. The likelihood of a plaque rupturing is thought to be asso...
Carotid Arteries Carotid Artery Diseases Carotid Stenosis Deep Learning Humans Image Processing, Computer-Assisted Neural Networks, Computer Plaque, Atherosclerotic
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Combining artificial intelligence assisted image segmentation and ultrasound based radiomics for the prediction of carotid plaque stability.

BMC medical imaging 40098096
PURPOSE: Utilizing artificial intelligence (AI) technology for the segmentation of plaques on ultrasound images to evaluate the stability of carotid artery plaques and analyze its diagnostic accuracy in differentiating vulnerable plaques from stable ...
Aged Artificial Intelligence Carotid Arteries Carotid Stenosis Female Humans Image Interpretation, Computer-Assisted Ischemic Stroke Male Middle Aged Plaque, Atherosclerotic Radiomics Retrospective Studies ROC Curve Sensitivity and Specificity Support Vector Machine Ultrasonography, Doppler, Color
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