AIMC Topic: Radiography, Thoracic

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Crowdsourcing airway annotations in chest computed tomography images.

PloS one Apr 22, 2021
Measuring airways in chest computed tomography (CT) scans is important for characterizing diseases such as cystic fibrosis, yet very time-consuming to perform manually. Machine learning algorithms offer an alternative, but need large sets of annotate...
Radiography, Thoracic Crowdsourcing Humans Algorithms Machine Learning Tomography, X-Ray Computed Lung
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Deep learning to detect acute respiratory distress syndrome on chest radiographs: a retrospective study with external validation.

The Lancet. Digital health Apr 20, 2021
BACKGROUND: Acute respiratory distress syndrome (ARDS) is a common, but under-recognised, critical illness syndrome associated with high mortality. An important factor in its under-recognition is the variability in chest radiograph interpretation for...
Respiratory Distress Syndrome Area Under Curve Radiography Radiographic Image Interpretation, Computer-Assisted Hospitals Deep Learning United States Pleural Diseases Datasets as Topic Radiography, Thoracic Pleural Cavity Algorithms Retrospective Studies Female Middle Aged Lung Aged Male Humans Neural Networks, Computer
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Classification of COVID-19 Chest CT Images Based on Ensemble Deep Learning.

Journal of healthcare engineering Apr 20, 2021
Novel coronavirus pneumonia (NCP) has become a global pandemic disease, and computed tomography-based (CT) image analysis and recognition are one of the important tools for clinical diagnosis. In order to assist medical personnel to achieve an effici...
SARS-CoV-2 Algorithms Humans Radiographic Image Interpretation, Computer-Assisted Sensitivity and Specificity Databases, Factual Pandemics Radiography, Thoracic Deep Learning Tomography, X-Ray Computed COVID-19
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Data valuation for medical imaging using Shapley value and application to a large-scale chest X-ray dataset.

Scientific reports Apr 16, 2021
The reliability of machine learning models can be compromised when trained on low quality data. Many large-scale medical imaging datasets contain low quality labels extracted from sources such as medical reports. Moreover, images within a dataset may...
Humans Neural Networks, Computer Machine Learning Diagnostic Imaging Datasets as Topic Radiography, Thoracic Algorithms Image Processing, Computer-Assisted Pneumonia
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GraphCovidNet: A graph neural network based model for detecting COVID-19 from CT scans and X-rays of chest.

Scientific reports Apr 15, 2021
COVID-19, a viral infection originated from Wuhan, China has spread across the world and it has currently affected over 115 million people. Although vaccination process has already started, reaching sufficient availability will take time. Considering...
Neural Networks, Computer COVID-19 Tomography, X-Ray Computed Radiography, Thoracic SARS-CoV-2 Humans Datasets as Topic
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Accessory pathway analysis using a multimodal deep learning model.

Scientific reports Apr 13, 2021
Cardiac accessory pathways (APs) in Wolff-Parkinson-White (WPW) syndrome are conventionally diagnosed with decision tree algorithms; however, there are problems with clinical usage. We assessed the efficacy of the artificial intelligence model using ...
Female Young Adult Adult Male Neural Networks, Computer Algorithms Retrospective Studies Electrocardiography Radiography, Thoracic Wolff-Parkinson-White Syndrome Humans Accessory Atrioventricular Bundle Middle Aged Deep Learning Adolescent
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BS-Net: Learning COVID-19 pneumonia severity on a large chest X-ray dataset.

Medical image analysis Mar 31, 2021
In this work we design an end-to-end deep learning architecture for predicting, on Chest X-rays images (CXR), a multi-regional score conveying the degree of lung compromise in COVID-19 patients. Such semi-quantitative scoring system, namely Brixia sc...
Humans COVID-19 X-Rays SARS-CoV-2 Deep Learning Radiography, Thoracic
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Pneumothorax detection in chest radiographs: optimizing artificial intelligence system for accuracy and confounding bias reduction using in-image annotations in algorithm training.

European radiology Mar 27, 2021
OBJECTIVES: Diagnostic accuracy of artificial intelligence (AI) pneumothorax (PTX) detection in chest radiographs (CXR) is limited by the noisy annotation quality of public training data and confounding thoracic tubes (TT). We hypothesize that in-ima...
Pneumothorax Radiography Radiography, Thoracic Data Curation Humans Artificial Intelligence Algorithms
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Prognostication of patients with COVID-19 using artificial intelligence based on chest x-rays and clinical data: a retrospective study.

The Lancet. Digital health Mar 24, 2021
BACKGROUND: Chest x-ray is a relatively accessible, inexpensive, fast imaging modality that might be valuable in the prognostication of patients with COVID-19. We aimed to develop and evaluate an artificial intelligence system using chest x-rays and ...
Prognosis Retrospective Studies Tomography, X-Ray Computed Aged Aged, 80 and over Female SARS-CoV-2 Humans Artificial Intelligence COVID-19 Middle Aged Young Adult United States Severity of Illness Index Adult Radiography, Thoracic Male
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Added Value of Deep Learning-based Detection System for Multiple Major Findings on Chest Radiographs: A Randomized Crossover Study.

Radiology Mar 23, 2021
Background Previous studies assessing the effects of computer-aided detection on observer performance in the reading of chest radiographs used a sequential reading design that may have biased the results because of reading order or recall bias. Purpo...
Observer Variation Radiography, Thoracic Deep Learning Lung Diseases Cross-Over Studies Humans Male Retrospective Studies Middle Aged Republic of Korea Female Sensitivity and Specificity
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