AIMC Topic: Radiography, Thoracic
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Bone suppression on pediatric chest radiographs via a deep learning-based cascade model.
Computer methods and programs in biomedicine
Jan 10, 2022
BACKGROUND AND OBJECTIVE: Bone suppression images (BSIs) of chest radiographs (CXRs) have been proven to improve diagnosis of pulmonary diseases. To acquire BSIs, dual-energy subtraction (DES) or a deep-learning-based model trained with DES-based BSI...
Attention based automated radiology report generation using CNN and LSTM.
PloS one
Jan 6, 2022
The automated generation of radiology reports provides X-rays and has tremendous potential to enhance the clinical diagnosis of diseases in patients. A new research direction is gaining increasing attention that involves the use of hybrid approaches ...
Bayesian-based optimized deep learning model to detect COVID-19 patients using chest X-ray image data.
Computers in biology and medicine
Jan 5, 2022
Coronavirus Disease 2019 (COVID-19) is extremely infectious and rapidly spreading around the globe. As a result, rapid and precise identification of COVID-19 patients is critical. Deep Learning has shown promising performance in a variety of domains ...
Diagnostic effect of artificial intelligence solution for referable thoracic abnormalities on chest radiography: a multicenter respiratory outpatient diagnostic cohort study.
European radiology
Jan 1, 2022
OBJECTIVES: We aim ed to evaluate a commercial artificial intelligence (AI) solution on a multicenter cohort of chest radiographs and to compare physicians' ability to detect and localize referable thoracic abnormalities with and without AI assistanc...
Independent evaluation of 12 artificial intelligence solutions for the detection of tuberculosis.
Scientific reports
Dec 13, 2021
There have been few independent evaluations of computer-aided detection (CAD) software for tuberculosis (TB) screening, despite the rapidly expanding array of available CAD solutions. We developed a test library of chest X-ray (CXR) images which was ...
Underdiagnosis bias of artificial intelligence algorithms applied to chest radiographs in under-served patient populations.
Nature medicine
Dec 10, 2021
Artificial intelligence (AI) systems have increasingly achieved expert-level performance in medical imaging applications. However, there is growing concern that such AI systems may reflect and amplify human bias, and reduce the quality of their perfo...
xViTCOS: Explainable Vision Transformer Based COVID-19 Screening Using Radiography.
IEEE journal of translational engineering in health and medicine
Dec 8, 2021
Since its outbreak, the rapid spread of COrona VIrus Disease 2019 (COVID-19) across the globe has pushed the health care system in many countries to the verge of collapse. Therefore, it is imperative to correctly identify COVID-19 positive patients ...
Do comprehensive deep learning algorithms suffer from hidden stratification? A retrospective study on pneumothorax detection in chest radiography.
BMJ open
Dec 7, 2021
OBJECTIVES: To evaluate the ability of a commercially available comprehensive chest radiography deep convolutional neural network (DCNN) to detect simple and tension pneumothorax, as stratified by the following subgroups: the presence of an intercost...
Deep learning computer-aided detection system for pneumonia in febrile neutropenia patients: a diagnostic cohort study.
BMC pulmonary medicine
Dec 7, 2021
BACKGROUND: Diagnosis of pneumonia is critical in managing patients with febrile neutropenia (FN), however, chest X-ray (CXR) has limited performance in the detection of pneumonia. We aimed to evaluate the performance of a deep learning-based compute...
Validation of expert system enhanced deep learning algorithm for automated screening for COVID-Pneumonia on chest X-rays.
Scientific reports
Dec 1, 2021
SARS-CoV2 pandemic exposed the limitations of artificial intelligence based medical imaging systems. Earlier in the pandemic, the absence of sufficient training data prevented effective deep learning (DL) solutions for the diagnosis of COVID-19 based...
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