AIMC Topic: Radiography, Thoracic

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Multi-Label Local to Global Learning: A Novel Learning Paradigm for Chest X-Ray Abnormality Classification.

IEEE journal of biomedical and health informatics Sep 6, 2023
Deep neural network (DNN) approaches have shown remarkable progress in automatic Chest X-rays classification. However, existing methods use a training scheme that simultaneously trains all abnormalities without considering their learning priority. In...
Humans Neural Networks, Computer Datasets as Topic Radiography, Thoracic X-Rays Machine Learning Models, Biological
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Use of artificial intelligence in triaging of chest radiographs to reduce radiologists' workload.

European radiology Aug 24, 2023
OBJECTIVES: To evaluate whether deep learning-based detection algorithms (DLD)-based triaging can reduce outpatient chest radiograph interpretation workload while maintaining noninferior sensitivity.
Adult Sensitivity and Specificity Middle Aged Retrospective Studies Aged Radiography Radiologists Workload Deep Learning Triage Humans Radiography, Thoracic Artificial Intelligence
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Learning from the machine: AI assistance is not an effective learning tool for resident education in chest x-ray interpretation.

European radiology Aug 12, 2023
OBJECTIVES: To assess whether a computer-aided detection (CADe) system could serve as a learning tool for radiology residents in chest X-ray (CXR) interpretation.
X-Rays Internship and Residency Artificial Intelligence Radiography Radiography, Thoracic Humans
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Training certified detectives to track down the intrinsic shortcuts in COVID-19 chest x-ray data sets.

Scientific reports Aug 4, 2023
Deep learning faces a significant challenge wherein the trained models often underperform when used with external test data sets. This issue has been attributed to spurious correlations between irrelevant features in the input data and corresponding ...
X-Rays Radiographic Image Interpretation, Computer-Assisted COVID-19 Humans Deep Learning Radiography, Thoracic
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Deep learning-based automatic detection for pulmonary nodules on chest radiographs: The relationship with background lung condition, nodule characteristics, and location.

European journal of radiology Jul 22, 2023
PURPOSE: Computer-aided diagnosis (CAD), which assists in the interpretation of chest radiographs, is becoming common. However, few studies have evaluated the benefits and pitfalls of CAD in the real world. This study aimed to evaluate the independen...
Radiography, Thoracic Lung Neoplasms Multiple Pulmonary Nodules Radiography Radiographic Image Interpretation, Computer-Assisted Solitary Pulmonary Nodule Sensitivity and Specificity Humans Lung Algorithms Deep Learning
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Opportunistic detection of type 2 diabetes using deep learning from frontal chest radiographs.

Nature communications Jul 7, 2023
Deep learning (DL) models can harness electronic health records (EHRs) to predict diseases and extract radiologic findings for diagnosis. With ambulatory chest radiographs (CXRs) frequently ordered, we investigated detecting type 2 diabetes (T2D) by ...
Diabetes Mellitus, Type 2 Radiography Radiography, Thoracic Prospective Studies Deep Learning Humans
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ConvCoroNet: a deep convolutional neural network optimized with iterative thresholding algorithm for Covid-19 detection using chest X-ray images.

Journal of biomolecular structure & dynamics Jun 24, 2023
Covid-19 is a global pandemic. Early and accurate detection of positive cases prevent the further spread of this epidemic and help to treat rapidly the infected patients. During the peak of this epidemic, there was an insufficiency of Covid-19 test k...
Neural Networks, Computer COVID-19 Algorithms Radiography, Thoracic SARS-CoV-2 Humans Sensitivity and Specificity
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POLCOVID: a multicenter multiclass chest X-ray database (Poland, 2020-2021).

Scientific data Jun 2, 2023
The outbreak of the SARS-CoV-2 pandemic has put healthcare systems worldwide to their limits, resulting in increased waiting time for diagnosis and required medical assistance. With chest radiographs (CXR) being one of the most common COVID-19 diagno...
Deep Learning Humans Pneumonia Artificial Intelligence SARS-CoV-2 COVID-19 Radiography, Thoracic COVID-19 Testing Poland X-Rays Algorithms
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Deep learning to estimate lung disease mortality from chest radiographs.

Nature communications May 16, 2023
Prevention and management of chronic lung diseases (asthma, lung cancer, etc.) are of great importance. While tests are available for reliable diagnosis, accurate identification of those who will develop severe morbidity/mortality is currently limite...
Humans Thorax Lung Lung Diseases Radiography, Thoracic Deep Learning
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Lightweight multi-scale classification of chest radiographs via size-specific batch normalization.

Computer methods and programs in biomedicine Apr 18, 2023
BACKGROUND AND OBJECTIVE: Convolutional neural networks are widely used to detect radiological findings in chest radiographs. Standard architectures are optimized for images of relatively small size (for example, 224 × 224 pixels), which suffices for...
Radiography Radiography, Thoracic Neural Networks, Computer Deep Learning
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