AI Medical Compendium Journal:
Cardiovascular and interventional radiology

Showing 1 to 10 of 23 articles

IR-GPT: AI Foundation Models to Optimize Interventional Radiology.

Cardiovascular and interventional radiology Mar 26, 2025
Foundation artificial intelligence (AI) models are capable of complex tasks that involve text, medical images, and many other types of data, but have not yet been customized for procedural medicine. This report reviews prior work in deep learning rel...
Radiology, Interventional Humans Artificial Intelligence Deep Learning
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Predicting Survival and Recurrence of Lung Ablation Patients Using Deep Learning-Based Automatic Segmentation and Radiomics Analysis.

Cardiovascular and interventional radiology Nov 27, 2024
PURPOSE: To predict survival and tumor recurrence following image-guided thermal ablation (IGTA) of lung tumors segmented using a deep learning approach.
Humans Retrospective Studies Lung Radiomics Deep Learning Male Lung Neoplasms Surgery, Computer-Assisted Middle Aged Neoplasm Recurrence, Local Tomography, X-Ray Computed Ablation Techniques Female Aged
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Beyond MELD Score: Association of Machine Learning-derived CT Body Composition with 90-Day Mortality Post Transjugular Intrahepatic Portosystemic Shunt Placement.

Cardiovascular and interventional radiology Oct 29, 2024
PURPOSE: To determine the association of machine learning-derived CT body composition and 90-day mortality after transjugular intrahepatic portosystemic shunt (TIPS) and to assess its predictive performance as a complement to Model for End-Stage Live...
Tomography, X-Ray Computed Female Aged Humans Machine Learning Retrospective Studies Predictive Value of Tests Body Composition Portasystemic Shunt, Transjugular Intrahepatic End Stage Liver Disease Male Middle Aged Risk Assessment
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Commentary on Machine Learning to Predict Prostate Artery Embolization Outcomes? Patient Selection for Prostatic Artery Embolization: Why it Matters.

Cardiovascular and interventional radiology Aug 19, 2024
Prostate Patient Selection Embolization, Therapeutic Humans Machine Learning Male Treatment Outcome Prostatic Hyperplasia
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Commentary: Detection of Endoleak After Endovascular Aortic Repair Through Deep Learning Based on Non-contrast CT.

Cardiovascular and interventional radiology Aug 7, 2024
Humans Tomography, X-Ray Computed Deep Learning Endovascular Aneurysm Repair Blood Vessel Prosthesis Implantation Endovascular Procedures Endoleak
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Detection of Endoleak after Endovascular Aortic Repair through Deep Learning Based on Non-contrast CT.

Cardiovascular and interventional radiology Jul 8, 2024
OBJECTIVES: To develop and validate a deep learning model for detecting post-endovascular aortic repair (EVAR) endoleak from non-contrast CT.
Endovascular Aneurysm Repair Endovascular Procedures Computed Tomography Angiography Endoleak Predictive Value of Tests Aortic Aneurysm, Abdominal Blood Vessel Prosthesis Implantation Retrospective Studies Female Aged Humans Aged, 80 and over Male Deep Learning
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Machine Learning to Predict Prostate Artery Embolization Outcomes.

Cardiovascular and interventional radiology Jun 19, 2024
PURPOSE: This study leverages pre-procedural data and machine learning (ML) techniques to predict outcomes at one year following prostate artery embolization (PAE).
Humans Machine Learning Retrospective Studies Aged Male Middle Aged Registries Embolization, Therapeutic Treatment Outcome Prostatic Hyperplasia Prostate
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Robotic Guided Interventional Radiology Set to Break Boundaries.

Cardiovascular and interventional radiology May 30, 2024
Robotics Radiography, Interventional Radiology, Interventional Humans
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Artificial Intelligence in the Angio-suite: Will Algorithms be the Copilots of the Interventional Radiologist?

Cardiovascular and interventional radiology May 15, 2024
Humans Algorithms Radiology, Interventional Artificial Intelligence Radiography, Interventional Angiography
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Artificial Intelligence for Identification of Images with Active Bleeding in Mesenteric and Celiac Arteries Angiography.

Cardiovascular and interventional radiology Mar 26, 2024
PURPOSE: The purpose of this study is to evaluate the efficacy of an artificial intelligence (AI) model designed to identify active bleeding in digital subtraction angiography images for upper gastrointestinal bleeding.
Angiography, Digital Subtraction Aged Mesenteric Arteries Adult Embolization, Therapeutic Humans Sensitivity and Specificity Celiac Artery Artificial Intelligence Algorithms Gastrointestinal Hemorrhage Male Retrospective Studies Female Middle Aged Radiographic Image Interpretation, Computer-Assisted
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