AIMC Topic: Pulmonary Embolism

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Development and Performance of the Pulmonary Embolism Result Forecast Model (PERFORM) for Computed Tomography Clinical Decision Support.

JAMA network open Aug 2, 2019
IMPORTANCE: Pulmonary embolism (PE) is a life-threatening clinical problem, and computed tomographic imaging is the standard for diagnosis. Clinical decision support rules based on PE risk-scoring models have been developed to compute pretest probabi...
Retrospective Studies Tomography, X-Ray Computed Electronic Health Records Reproducibility of Results Humans Machine Learning Middle Aged Risk Assessment Decision Support Systems, Clinical Pulmonary Embolism Aged Aged, 80 and over Adult
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Comparative effectiveness of convolutional neural network (CNN) and recurrent neural network (RNN) architectures for radiology text report classification.

Artificial intelligence in medicine Nov 23, 2018
This paper explores cutting-edge deep learning methods for information extraction from medical imaging free text reports at a multi-institutional scale and compares them to the state-of-the-art domain-specific rule-based system - PEFinder and traditi...
Humans Radiography, Thoracic Pulmonary Embolism Information Storage and Retrieval Neural Networks, Computer Deep Learning
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Autonomous detection, grading, and reporting of postoperative complications using natural language processing.

Surgery Jul 26, 2018
INTRODUCTION: Natural language processing, a computer science technique that allows interpretation of narrative text, is infrequently used to identify surgical complications. We designed a natural language processing algorithm to identify and grade t...
Venous Thromboembolism Venous Thrombosis Quality Improvement Natural Language Processing Pulmonary Embolism Humans Algorithms Postoperative Complications
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Evaluating Report Text Variation and Informativeness: Natural Language Processing of CT Chest Imaging for Pulmonary Embolism.

Journal of the American College of Radiology : JACR Feb 13, 2018
OBJECTIVE: The aim of this study was to quantify the variability of language in free text reports of pulmonary embolus (PE) studies and to gauge the informativeness of free text to predict PE diagnosis using machine learning as proxy for human unders...
Humans Machine Learning Software Natural Language Processing Pulmonary Embolism Data Mining Documentation Retrospective Studies Tomography, X-Ray Computed Contrast Media
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Radiology report annotation using intelligent word embeddings: Applied to multi-institutional chest CT cohort.

Journal of biomedical informatics Nov 23, 2017
We proposed an unsupervised hybrid method - Intelligent Word Embedding (IWE) that combines neural embedding method with a semantic dictionary mapping technique for creating a dense vector representation of unstructured radiology reports. We applied I...
Pulmonary Embolism Semantics Radiography, Thoracic Predictive Value of Tests Natural Language Processing Radiographic Image Interpretation, Computer-Assisted Machine Learning Tomography, X-Ray Computed Humans Neural Networks, Computer
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Deep Learning to Classify Radiology Free-Text Reports.

Radiology Nov 13, 2017
Purpose To evaluate the performance of a deep learning convolutional neural network (CNN) model compared with a traditional natural language processing (NLP) model in extracting pulmonary embolism (PE) findings from thoracic computed tomography (CT) ...
Radiography, Thoracic ROC Curve Natural Language Processing Pulmonary Embolism Humans Neural Networks, Computer Machine Learning Reproducibility of Results Sensitivity and Specificity Algorithms Tomography, X-Ray Computed
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The safety and efficacy of full- versus reduced-dose betrixaban in the Acute Medically Ill VTE (Venous Thromboembolism) Prevention With Extended-Duration Betrixaban (APEX) trial.

American heart journal Dec 18, 2016
BACKGROUND: The APEX trial assessed the safety and efficacy of extended-duration thromboprophylaxis using betrixaban versus standard dosing of enoxaparin among hospitalized, acutely ill medical patients. The 80-mg betrixaban dose was halved to 40 mg ...
Enoxaparin Venous Thrombosis Factor Xa Inhibitors Aged Pyridines Humans Benzamides Hemorrhage Aged, 80 and over Anticoagulants Double-Blind Method Venous Thromboembolism Female Male Pulmonary Embolism Hospitalization
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Mapping Phenotypic Information in Heterogeneous Textual Sources to a Domain-Specific Terminological Resource.

PloS one Sep 19, 2016
Biomedical literature articles and narrative content from Electronic Health Records (EHRs) both constitute rich sources of disease-phenotype information. Phenotype concepts may be mentioned in text in multiple ways, using phrases with a variety of st...
Natural Language Processing Pulmonary Embolism Heart Failure Unified Medical Language System Vocabulary, Controlled Data Mining Semantics Phenotype Electronic Health Records Narration Humans
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Convolutional Neural Networks for Medical Image Analysis: Full Training or Fine Tuning?

IEEE transactions on medical imaging Mar 7, 2016
Training a deep convolutional neural network (CNN) from scratch is difficult because it requires a large amount of labeled training data and a great deal of expertise to ensure proper convergence. A promising alternative is to fine-tune a CNN that ha...
Colonic Polyps Image Interpretation, Computer-Assisted Computed Tomography Angiography Colonoscopy Diagnostic Imaging Humans ROC Curve Pulmonary Embolism Neural Networks, Computer Machine Learning
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Neural hypernetwork approach for pulmonary embolism diagnosis.

BMC research notes Oct 29, 2015
BACKGROUND: Hypernetworks are based on topological simplicial complexes and generalize the concept of two-body relation to many-body relation. Furthermore, Hypernetworks provide a significant generalization of network theory, enabling the integration...
Humans Pulmonary Embolism Neural Networks, Computer Survival Analysis Middle Aged Machine Learning Lung Female Ultrasonography Aged ROC Curve Male
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