AI Medical Compendium Journal:
Journal of vascular and interventional radiology : JVIR

Showing 21 to 27 of 27 articles

Machine Learning Offers Exciting Potential for Predicting Postprocedural Outcomes: A Framework for Developing Random Forest Models in IR.

Journal of vascular and interventional radiology : JVIR May 4, 2020
PURPOSE: To demonstrate that random forest models trained on a large national sample can accurately predict relevant outcomes and may ultimately contribute to future clinical decision support tools in IR.
Child, Preschool Child Hospital Mortality United States Infant Length of Stay Adolescent Time Factors Portasystemic Shunt, Transjugular Intrahepatic Iatrogenic Disease Pneumothorax Uterine Artery Embolization Inpatients Data Mining Radiography, Interventional Risk Factors Image-Guided Biopsy Databases, Factual Aged Retrospective Studies Aged, 80 and over Adult Female Young Adult Male Infant, Newborn Middle Aged Risk Assessment Humans Machine Learning
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Deep Learning for Automated Classification of Inferior Vena Cava Filter Types on Radiographs.

Journal of vascular and interventional radiology : JVIR Sep 18, 2019
PURPOSE: To demonstrate the feasibility and evaluate the performance of a deep-learning convolutional neural network (CNN) classification model for automated identification of different types of inferior vena cava (IVC) filters on radiographs.
Humans Prospective Studies Reproducibility of Results Prosthesis Design Automation Vena Cava, Inferior Phlebography Deep Learning Predictive Value of Tests Radiographic Image Interpretation, Computer-Assisted Registries Prosthesis Implantation Vena Cava Filters
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The Role of Artificial Intelligence in Interventional Oncology: A Primer.

Journal of vascular and interventional radiology : JVIR Dec 7, 2018
Radiography, Interventional Forecasting Clinical Decision-Making Diagnosis, Computer-Assisted Liver Neoplasms Humans Workflow Neural Networks, Computer Patient Selection Artificial Intelligence Diffusion of Innovation Machine Learning Medical Oncology
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Evaluation of a CT-Guided Robotic System for Precise Percutaneous Needle Insertion.

Journal of vascular and interventional radiology : JVIR Apr 6, 2018
PURPOSE: To assess overall targeting accuracy for CT-guided needle insertion using prototype robotic system for common target sites.
Kidney Liver Robotics Equipment Design Materials Testing Models, Animal Retroperitoneal Space Needles Tomography, X-Ray Computed Female Animals Radiography, Interventional Image-Guided Biopsy Sus scrofa Bronchi
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Predicting Treatment Response to Intra-arterial Therapies for Hepatocellular Carcinoma with the Use of Supervised Machine Learning-An Artificial Intelligence Concept.

Journal of vascular and interventional radiology : JVIR Mar 14, 2018
PURPOSE: To use magnetic resonance (MR) imaging and clinical patient data to create an artificial intelligence (AI) framework for the prediction of therapeutic outcomes of transarterial chemoembolization by applying machine learning (ML) techniques.
Ethiodized Oil Neoplasm Staging Doxorubicin Chemoembolization, Therapeutic Aged Adult Sensitivity and Specificity Male Treatment Outcome Humans Contrast Media Middle Aged Machine Learning Magnetic Resonance Imaging Retrospective Studies Antineoplastic Agents Predictive Value of Tests Female Liver Neoplasms Carcinoma, Hepatocellular
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The Pivotal Multicenter Trial of Ultrasound-Guided Percutaneous Arteriovenous Fistula Creation for Hemodialysis Access.

Journal of vascular and interventional radiology : JVIR Dec 21, 2017
PURPOSE: To evaluate safety and efficacy of arteriovenous fistulas (AVFs) created with a thermal resistance anastomosis device.
Middle Aged Renal Dialysis Ultrasonography, Interventional Platelet Aggregation Inhibitors Humans Aged Radial Artery Prospective Studies Aged, 80 and over Brachial Artery Female Adult Blood Flow Velocity Male Arteriovenous Shunt, Surgical
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Nomogram and Artificial Neural Network for Prognostic Performance on the Albumin-Bilirubin Grade for Hepatocellular Carcinoma Undergoing Transarterial Chemoembolization.

Journal of vascular and interventional radiology : JVIR Mar 1, 2019
PURPOSE: To construct the albumin-bilirubin (ALBI) grade and the Child-Turcotte-Pugh (CTP) score based on nomograms, as well as to develop an artificial neural network (ANN) to compare the prognostic performance of the 2 scores for hepatocellular car...
Serum Albumin, Human Treatment Outcome Neoplasm Grading Bilirubin Chemoembolization, Therapeutic Biomarkers, Tumor Male Middle Aged China Time Factors Liver Neoplasms Carcinoma, Hepatocellular Nomograms Decision Support Techniques Retrospective Studies Female Reproducibility of Results Humans Neural Networks, Computer
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