AIMC Topic: Radiography, Thoracic

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Artificial intelligence's contribution to early pulmonary lesion detection in chest X-rays: insights from two retrospective studies on a Czech population.

Casopis lekaru ceskych Jan 1, 2024
In recent years healthcare is undergoing significant changes due to technological innovations, with Artificial Intelligence (AI) being a key trend. Particularly in radiodiagnostics, according to studies, AI has the potential to enhance accuracy and e...
Artificial Intelligence Retrospective Studies Sensitivity and Specificity Humans Czech Republic Radiography, Thoracic Deep Learning Lung Neoplasms Early Detection of Cancer
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Predicting patient-specific organ doses from thoracic CT examinations using support vector regression algorithm.

Journal of X-ray science and technology Jan 1, 2024
PURPOSE: This study aims to propose and develop a fast, accurate, and robust prediction method of patient-specific organ doses from CT examinations using minimized computational resources.
Humans Middle Aged Lung Support Vector Machine Radiation Dosage Radiography, Thoracic Monte Carlo Method Aged Adult Male Algorithms Tomography, X-Ray Computed Female
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DDA-SSNets: Dual decoder attention-based semantic segmentation networks for COVID-19 infection segmentation and classification using chest X-Ray images.

Journal of X-ray science and technology Jan 1, 2024
BACKGROUND: COVID-19 needs to be diagnosed and staged to be treated accurately. However, prior studies' diagnostic and staging abilities for COVID-19 infection needed to be improved. Therefore, new deep learning-based approaches are required to aid r...
COVID-19 Algorithms SARS-CoV-2 Humans Neural Networks, Computer Pandemics Semantics Radiography, Thoracic Betacoronavirus Pneumonia, Viral Lung Deep Learning Coronavirus Infections
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Commercially Available Chest Radiograph AI Tools for Detecting Airspace Disease, Pneumothorax, and Pleural Effusion.

Radiology Sep 1, 2023
Background Commercially available artificial intelligence (AI) tools can assist radiologists in interpreting chest radiographs, but their real-life diagnostic accuracy remains unclear. Purpose To evaluate the diagnostic accuracy of four commercially ...
Radiography, Thoracic Pneumothorax Female Aged Adult Sensitivity and Specificity Deep Learning Pleural Effusion Humans Artificial Intelligence Retrospective Studies
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Deep Learning-Enabled Detection of Pneumoperitoneum in Supine and Erect Abdominal Radiography: Modeling Using Transfer Learning and Semi-Supervised Learning.

Korean journal of radiology Jun 1, 2023
OBJECTIVE: Detection of pneumoperitoneum using abdominal radiography, particularly in the supine position, is often challenging. This study aimed to develop and externally validate a deep learning model for the detection of pneumoperitoneum using sup...
Supervised Machine Learning Radiography, Thoracic Radiography, Abdominal Deep Learning Radiography Humans Retrospective Studies
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Artificial Intelligence Solution for Chest Radiographs in Respiratory Outpatient Clinics: Multicenter Prospective Randomized Clinical Trial.

Annals of the American Thoracic Society May 1, 2023
Artificial intelligence (AI)-assisted diagnosis imparts high accuracy to chest radiography (CXR) interpretation; however, its benefit for nonradiologist physicians in detecting lung lesions on CXR remains unclear. To investigate whether AI assistan...
Lung Radiography Radiography, Thoracic Humans Artificial Intelligence Prospective Studies
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Effects of Expert-Determined Reference Standards in Evaluating the Diagnostic Performance of a Deep Learning Model: A Malignant Lung Nodule Detection Task on Chest Radiographs.

Korean journal of radiology Feb 1, 2023
OBJECTIVE: Little is known about the effects of using different expert-determined reference standards when evaluating the performance of deep learning-based automatic detection (DLAD) models and their added value to radiologists. We assessed the conc...
Artificial Intelligence Retrospective Studies Sensitivity and Specificity Lung Deep Learning Lung Neoplasms Humans Radiographic Image Interpretation, Computer-Assisted Reference Standards Radiography, Thoracic
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Automatic Localization and Identification of Thoracic Diseases from Chest X-rays with Deep Learning.

Current medical imaging Jan 1, 2022
BACKGROUND: There are numerous difficulties in using deep learning to automatically locate and identify diseases in chest X-rays (CXR). The most prevailing two are the lack of labeled data of disease locations and poor model transferability between d...
Radiography, Thoracic Humans Deep Learning X-Rays Radiographic Image Interpretation, Computer-Assisted Thoracic Diseases
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The diagnostic performance of deep-learning-based CT severity score to identify COVID-19 pneumonia.

The British journal of radiology Jan 1, 2022
OBJECTIVE: To determine the diagnostic accuracy of a deep-learning (DL)-based algorithm using chest computed tomography (CT) scans for the rapid diagnosis of coronavirus disease 2019 (COVID-19), as compared to the reference standard reverse-transcrip...
Male Severity of Illness Index Deep Learning Aged Adult Sensitivity and Specificity Radiography, Thoracic Image Processing, Computer-Assisted False Negative Reactions Humans False Positive Reactions Tomography, X-Ray Computed COVID-19 Female Retrospective Studies Reproducibility of Results
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An Efficient Method for Coronavirus Detection Through X-rays Using Deep Neural Network.

Current medical imaging Jan 1, 2022
BACKGROUND: Coronavirus (COVID-19) is a group of infectious diseases caused by related viruses called coronaviruses. In humans, the seriousness of infection caused by a coronavirus in the respiratory tract can vary from mild to lethal. A serious illn...
Humans Radiography, Thoracic Neural Networks, Computer X-Rays COVID-19 SARS-CoV-2 Deep Learning
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