AIMC Topic: Aortic Dissection

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Exploratory analysis of Type B Aortic Dissection (TBAD) segmentation in 2D CTA images using various kernels.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society Nov 18, 2024
Type-B Aortic Dissection is a rare but fatal cardiovascular disease characterized by a tear in the inner layer of the aorta, affecting 3.5 per 100,000 individuals annually. In this work, we explore the feasibility of leveraging two-dimensional Convol...
Humans Neural Networks, Computer Radiographic Image Interpretation, Computer-Assisted Aortic Dissection Computed Tomography Angiography
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Machine Learning Model for Predicting Risk Factors of Prolonged Length of Hospital Stay in Patients with Aortic Dissection: a Retrospective Clinical Study.

Journal of cardiovascular translational research Oct 10, 2024
The length of hospital stay (LOS) is crucial for assessing medical service quality. This study aimed to develop machine learning models for predicting risk factors of prolonged LOS in patients with aortic dissection (AD). The data of 516 AD patients ...
Female Risk Factors Aged Adult Humans Machine Learning Decision Support Techniques Retrospective Studies Time Factors Male Predictive Value of Tests Middle Aged Aortic Dissection Risk Assessment Aortic Aneurysm Length of Stay
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Enhanced machine learning models for predicting one-year mortality in individuals suffering from type A aortic dissection.

The Journal of thoracic and cardiovascular surgery Sep 18, 2024
OBJECTIVE: The study objective was to develop and validate an interpretable machine learning model to predict 1-year mortality in patients with type A aortic dissection, improving risk classification and aiding clinical decision-making.
Decision Support Techniques Prognosis Retrospective Studies Clinical Decision-Making Humans Machine Learning Predictive Value of Tests Male Female Aortic Dissection Middle Aged Risk Factors Aortic Aneurysm Risk Assessment Aged Time Factors
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Unraveling phenotypic heterogeneity in stanford type B aortic dissection patients through machine learning clustering analysis of cardiovascular CT imaging.

Hellenic journal of cardiology : HJC = Hellenike kardiologike epitheorese Aug 10, 2024
OBJECTIVE: Aortic dissection remains a life-threatening condition necessitating accurate diagnosis and timely intervention. This study aimed to investigate phenotypic heterogeneity in patients with Stanford type B aortic dissection (TBAD) through mac...
Middle Aged Imaging, Three-Dimensional Cluster Analysis Aortic Dissection Aged Adult Male Aortic Aneurysm, Thoracic Computed Tomography Angiography Humans Machine Learning Phenotype Retrospective Studies Tomography, X-Ray Computed Female
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Streamlining Acute Abdominal Aortic Dissection Management-An AI-based CT Imaging Workflow.

Journal of imaging informatics in medicine Jun 12, 2024
Life-threatening acute aortic dissection (AD) demands timely diagnosis for effective intervention. To streamline intrahospital workflows, automated detection of AD in abdominal computed tomography (CT) scans seems useful to assist humans. We aimed at...
Algorithms Retrospective Studies Tomography, X-Ray Computed Female Aged Male Middle Aged ROC Curve Humans Neural Networks, Computer Aortic Aneurysm, Abdominal Dissection, Abdominal Aorta Workflow Aortic Dissection
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Volumetric analysis of acute uncomplicated type B aortic dissection using an automated deep learning aortic zone segmentation model.

Journal of vascular surgery Jun 6, 2024
BACKGROUND: Machine learning techniques have shown excellent performance in three-dimensional medical image analysis, but have not been applied to acute uncomplicated type B aortic dissection (auTBAD) using Society for Vascular Surgery (SVS) and Soci...
Aortic Aneurysm Aortography Automation Aortic Dissection Aortic Aneurysm, Thoracic Computed Tomography Angiography Predictive Value of Tests Acute Disease Radiographic Image Interpretation, Computer-Assisted Reproducibility of Results Humans Aged Retrospective Studies Disease Progression Male Female Deep Learning Middle Aged Time Factors Imaging, Three-Dimensional
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Deep learning-based radiomics of computed tomography angiography to predict adverse events after initial endovascular repair for acute uncomplicated Stanford type B aortic dissection.

European journal of radiology Apr 15, 2024
PURPOSE: This study aimed to construct a predictive model integrating deep learning-derived radiomic features from computed tomography angiography (CTA) and clinical biomarkers to forecast postoperative adverse events (AEs) in patients with acute unc...
Endovascular Procedures Computed Tomography Angiography Acute Disease Aortic Dissection Aortic Aneurysm, Thoracic Humans Middle Aged Retrospective Studies Postoperative Complications Deep Learning Predictive Value of Tests Female Aged Radiomics Male
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Deep learning-based diagnosis of aortic dissection using an electrocardiogram: Development, validation, and clinical implications of the AADE score.

Kardiologia polska Jan 17, 2024
BACKGROUND: Aortic dissection (AD) is frequently associated with abnormalities in electrocardiographic findings. Advancements in medical technology present an opportunity to leverage these observations to improve patient diagnosis and care.
Chest Pain Aortic Dissection Artificial Intelligence Deep Learning Electrocardiography Humans
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Deep learning-based multi-stage postoperative type-b aortic dissection segmentation using global-local fusion learning.

Physics in medicine and biology Nov 29, 2023
Type-b aortic dissection (AD) is a life-threatening cardiovascular disease and the primary treatment is thoracic endovascular aortic repair (TEVAR). Due to the lack of a rapid and accurate segmentation technique, the patient-specific postoperative AD...
Retrospective Studies Aortic Aneurysm, Thoracic Humans Deep Learning Blood Vessel Prosthesis Implantation Treatment Outcome Endovascular Procedures Aortic Dissection
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Deep learning-aided extraction of outer aortic surface from CT angiography scans of patients with Stanford type B aortic dissection.

European radiology experimental Jun 29, 2023
BACKGROUND: Guidelines recommend that aortic dimension measurements in aortic dissection should include the aortic wall. This study aimed to evaluate two-dimensional (2D)- and three-dimensional (3D)-based deep learning approaches for extraction of ou...
Aortic Dissection Humans Aorta Retrospective Studies Computed Tomography Angiography Deep Learning
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