AIMC Topic: Radiography, Thoracic

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Automating chest radiograph imaging quality control.

Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB) Mar 23, 2021
PURPOSE: To automate diagnostic chest radiograph imaging quality control (lung inclusion at all four edges, patient rotation, and correct inspiration) using convolutional neural network models.
Radiography Quality Control Radiography, Thoracic Humans Neural Networks, Computer ROC Curve
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Role of Hybrid Deep Neural Networks (HDNNs), Computed Tomography, and Chest X-rays for the Detection of COVID-19.

International journal of environmental research and public health Mar 16, 2021
COVID-19 syndrome has extensively escalated worldwide with the induction of the year 2020 and has resulted in the illness of millions of people. COVID-19 patients bear an elevated risk once the symptoms deteriorate. Hence, early recognition of diseas...
Neural Networks, Computer COVID-19 Tomography, X-Ray Computed Humans Radiography, Thoracic SARS-CoV-2 X-Rays Deep Learning
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Can Artificial Intelligence Substitute Right-Heart Catheterization With Chest X-Rays?

The Canadian journal of cardiology Mar 9, 2021
Radiography, Thoracic Cardiac Catheterization X-Rays Humans Artificial Intelligence Radiography
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PSSPNN: PatchShuffle Stochastic Pooling Neural Network for an Explainable Diagnosis of COVID-19 with Multiple-Way Data Augmentation.

Computational and mathematical methods in medicine Mar 8, 2021
AIM: COVID-19 has caused large death tolls all over the world. Accurate diagnosis is of significant importance for early treatment.
Medical Informatics Radiography, Thoracic Stochastic Processes Databases, Factual Reproducibility of Results Pneumonia Software Humans Community-Acquired Infections Retrospective Studies Tuberculosis, Pulmonary Diagnosis, Computer-Assisted COVID-19 Tomography, X-Ray Computed Neural Networks, Computer Algorithms Imaging, Three-Dimensional
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COVID-19 Recognition Using Ensemble-CNNs in Two New Chest X-ray Databases.

Sensors (Basel, Switzerland) Mar 3, 2021
The recognition of COVID-19 infection from X-ray images is an emerging field in the learning and computer vision community. Despite the great efforts that have been made in this field since the appearance of COVID-19 (2019), the field still suffers f...
Neural Networks, Computer Humans COVID-19 Deep Learning Algorithms Radiography, Thoracic X-Rays
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Metaheuristic-based Deep COVID-19 Screening Model from Chest X-Ray Images.

Journal of healthcare engineering Mar 1, 2021
COVID-19 has affected the whole world drastically. A huge number of people have lost their lives due to this pandemic. Early detection of COVID-19 infection is helpful for treatment and quarantine. Therefore, many researchers have designed a deep lea...
Radiography, Thoracic COVID-19 Algorithms Deep Learning Humans Image Interpretation, Computer-Assisted Sensitivity and Specificity Neural Networks, Computer
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Convolutional neural network model based on radiological images to support COVID-19 diagnosis: Evaluating database biases.

PloS one Mar 1, 2021
As SARS-CoV-2 has spread quickly throughout the world, the scientific community has spent major efforts on better understanding the characteristics of the virus and possible means to prevent, diagnose, and treat COVID-19. A valid approach presented i...
COVID-19 Algorithms Databases, Factual Deep Learning Pneumonia Bias Humans Neural Networks, Computer Image Interpretation, Computer-Assisted Radiography, Thoracic
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Diagnosis of normal chest radiographs using an autonomous deep-learning algorithm.

Clinical radiology Feb 24, 2021
AIM: To evaluate the suitability of a deep-learning (DL) algorithm for identifying normality as a rule-out test for fully automated diagnosis in frontal adult chest radiographs (CXR) in an active clinical pathway.
Reproducibility of Results Deep Learning Image Processing, Computer-Assisted Algorithms Retrospective Studies Reference Values Radiography, Thoracic Humans
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COVID-19 Detection from Chest X-ray Images Using Feature Fusion and Deep Learning.

Sensors (Basel, Switzerland) Feb 20, 2021
Currently, COVID-19 is considered to be the most dangerous and deadly disease for the human body caused by the novel coronavirus. In December 2019, the coronavirus spread rapidly around the world, thought to be originated from Wuhan in China and is r...
Deep Learning China Image Interpretation, Computer-Assisted Radiography, Thoracic X-Rays Humans COVID-19
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Performance of a deep-learning algorithm for referable thoracic abnormalities on chest radiographs: A multicenter study of a health screening cohort.

PloS one Feb 19, 2021
PURPOSE: This study evaluated the performance of a commercially available deep-learning algorithm (DLA) (Insight CXR, Lunit, Seoul, South Korea) for referable thoracic abnormalities on chest X-ray (CXR) using a consecutively collected multicenter hea...
Radiography, Thoracic ROC Curve Multicenter Studies as Topic Female Aged Adult Humans Male Middle Aged Algorithms Deep Learning Retrospective Studies
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