AIMC Topic: Radiography, Thoracic

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Multi-population generalizability of a deep learning-based chest radiograph severity score for COVID-19.

Medicine Jul 22, 2022
To tune and test the generalizability of a deep learning-based model for assessment of COVID-19 lung disease severity on chest radiographs (CXRs) from different patient populations. A published convolutional Siamese neural network-based model previou...
Radiologists Radiography, Thoracic Lung Deep Learning Humans COVID-19
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Automated diagnosis and prognosis of COVID-19 pneumonia from initial ER chest X-rays using deep learning.

BMC infectious diseases Jul 21, 2022
BACKGROUND: Airspace disease as seen on chest X-rays is an important point in triage for patients initially presenting to the emergency department with suspected COVID-19 infection. The purpose of this study is to evaluate a previously trained interp...
Adult Deep Learning Radiography, Thoracic Tomography, X-Ray Computed SARS-CoV-2 X-Rays Humans Artificial Intelligence Prognosis Retrospective Studies COVID-19
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Simplified Transfer Learning for Chest Radiography Models Using Less Data.

Radiology Jul 19, 2022
Background Developing deep learning models for radiology requires large data sets and substantial computational resources. Data set size limitations can be further exacerbated by distribution shifts, such as rapid changes in patient populations and s...
Machine Learning Pandemics COVID-19 Humans Radiography Radiographic Image Interpretation, Computer-Assisted Radiography, Thoracic Retrospective Studies Deep Learning
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Automated detection of enteric tubes misplaced in the respiratory tract on chest radiographs using deep learning with two centre validation.

Clinical radiology Jul 15, 2022
AIM: To develop and test a model based on a convolutional neural network that can identify enteric tube position accurately on chest radiography.
Respiratory System Radiography Radiography, Thoracic Humans Adult Neural Networks, Computer Retrospective Studies Deep Learning
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Multi-center validation of an artificial intelligence system for detection of COVID-19 on chest radiographs in symptomatic patients.

European radiology Jul 2, 2022
OBJECTIVES: While chest radiograph (CXR) is the first-line imaging investigation in patients with respiratory symptoms, differentiating COVID-19 from other respiratory infections on CXR remains challenging. We developed and validated an AI system for...
Humans Tomography, X-Ray Computed Artificial Intelligence Deep Learning Radiography, Thoracic COVID-19 Retrospective Studies
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Successful Implementation of an Artificial Intelligence-Based Computer-Aided Detection System for Chest Radiography in Daily Clinical Practice.

Korean journal of radiology Jun 20, 2022
Radiography, Thoracic Artificial Intelligence Computers Radiography Humans
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Diagnostic performance of artificial intelligence approved for adults for the interpretation of pediatric chest radiographs.

Scientific reports Jun 17, 2022
Artificial intelligence (AI) applied to pediatric chest radiographs are yet scarce. This study evaluated whether AI-based software developed for adult chest radiographs can be used for pediatric chest radiographs. Pediatric patients (≤ 18 years old) ...
Humans Retrospective Studies Adult Artificial Intelligence Cardiomegaly Radiography, Thoracic Pneumothorax Sensitivity and Specificity Child Adolescent Child, Preschool Radiography
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ThoraciNet: thoracic abnormality detection and disease classification using fusion DCNNs.

Physical and engineering sciences in medicine May 30, 2022
Chest X-rays are arguably the de facto medical imaging technique for diagnosing thoracic abnormalities. Chest X-ray analysis is complex, especially in asymptomatic diseases, and relies heavily on the expertise of radiologists. This work proposes the ...
Radiography, Thoracic Databases, Factual Diagnosis, Computer-Assisted Radiography Humans Neural Networks, Computer
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Comparison of radiologist versus natural language processing-based image annotations for deep learning system for tuberculosis screening on chest radiographs.

Clinical imaging Apr 25, 2022
Although natural language processing (NLP) can rapidly extract disease labels from radiology reports to create datasets for deep learning models, this may be less accurate than having radiologists manually review the images. In this study, we compare...
Radiologists Radiography, Thoracic Deep Learning Data Curation Humans Natural Language Processing Retrospective Studies
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Pediatric chest radiograph interpretation: how far has artificial intelligence come? A systematic literature review.

Pediatric radiology Apr 23, 2022
Most artificial intelligence (AI) studies have focused primarily on adult imaging, with less attention to the unique aspects of pediatric imaging. The objectives of this study were to (1) identify all publicly available pediatric datasets and determi...
Child Pneumonia Radiography, Thoracic Algorithms Adult Humans Artificial Intelligence
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