AIMC Topic: Radiography, Thoracic

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Synthetic CT image generation of shape-controlled lung cancer using semi-conditional InfoGAN and its applicability for type classification.

International journal of computer assisted radiology and surgery Jan 11, 2021
PURPOSE: In recent years, convolutional neural network (CNN), an artificial intelligence technology with superior image recognition, has become increasingly popular and frequently used for classification tasks in medical imaging. However, the amount ...
Radiography, Thoracic Humans Neural Networks, Computer Artificial Intelligence Tomography, X-Ray Computed Lung Image Processing, Computer-Assisted Lung Neoplasms
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Chest X-ray image phase features for improved diagnosis of COVID-19 using convolutional neural network.

International journal of computer assisted radiology and surgery Jan 9, 2021
PURPOSE: Recently, the outbreak of the novel coronavirus disease 2019 (COVID-19) pandemic has seriously endangered human health and life. In fighting against COVID-19, effective diagnosis of infected patient is critical for preventing the spread of d...
Thorax Deep Learning Pneumonia Humans Radiography, Thoracic Pandemics Neural Networks, Computer COVID-19 Algorithms Tomography, X-Ray Computed
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Universal adversarial attacks on deep neural networks for medical image classification.

BMC medical imaging Jan 7, 2021
BACKGROUND: Deep neural networks (DNNs) are widely investigated in medical image classification to achieve automated support for clinical diagnosis. It is necessary to evaluate the robustness of medical DNN tasks against adversarial attacks, as high-...
Humans Diabetic Retinopathy Neural Networks, Computer Tomography, Optical Coherence Image Interpretation, Computer-Assisted Radiography, Thoracic Photography Skin Neoplasms Pneumonia Diagnostic Imaging
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A new resource on artificial intelligence powered computer automated detection software products for tuberculosis programmes and implementers.

Tuberculosis (Edinburgh, Scotland) Jan 4, 2021
Recently, the number of artificial intelligence powered computer-aided detection (CAD) products that detect tuberculosis (TB)-related abnormalities from chest X-rays (CXR) available on the market has increased. Although CXR is a relatively effective ...
Lung Diagnosis, Computer-Assisted Deep Learning Predictive Value of Tests Humans Software Reproducibility of Results Diffusion of Innovation Automation Host-Pathogen Interactions Radiography, Thoracic Radiographic Image Interpretation, Computer-Assisted Tuberculosis, Pulmonary Mycobacterium tuberculosis
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A Head-to Head Comparison of Machine Learning Algorithms for Identification of Implanted Cardiac Devices.

The American journal of cardiology Dec 29, 2020
Application of artificial intelligence techniques in medicine has rapidly expanded in recent years. Two algorithms for identification of cardiac implantable electronic devices using chest radiography were recently developed: The PacemakerID algorithm...
Radiography, Thoracic Defibrillators, Implantable Pacemaker, Artificial Machine Learning Algorithms Image Interpretation, Computer-Assisted Humans Neural Networks, Computer
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Transfer learning with chest X-rays for ER patient classification.

Scientific reports Dec 1, 2020
One of the challenges with urgent evaluation of patients with acute respiratory distress syndrome (ARDS) in the emergency room (ER) is distinguishing between cardiac vs infectious etiologies for their pulmonary findings. We conducted a retrospective ...
Retrospective Studies Deep Learning Respiratory Distress Syndrome Emergency Service, Hospital Radiography, Thoracic Patients Disease Humans
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Machine-learning classification of texture features of portable chest X-ray accurately classifies COVID-19 lung infection.

Biomedical engineering online Nov 25, 2020
BACKGROUND: The large volume and suboptimal image quality of portable chest X-rays (CXRs) as a result of the COVID-19 pandemic could post significant challenges for radiologists and frontline physicians. Deep-learning artificial intelligent (AI) meth...
COVID-19 Tomography, X-Ray Computed Image Processing, Computer-Assisted Lung Diseases Radiography, Thoracic Humans Machine Learning
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DeepCOVID-XR: An Artificial Intelligence Algorithm to Detect COVID-19 on Chest Radiographs Trained and Tested on a Large U.S. Clinical Data Set.

Radiology Nov 24, 2020
Background There are characteristic findings of coronavirus disease 2019 (COVID-19) on chest images. An artificial intelligence (AI) algorithm to detect COVID-19 on chest radiographs might be useful for triage or infection control within a hospital s...
Humans Artificial Intelligence Lung SARS-CoV-2 United States COVID-19 Datasets as Topic Sensitivity and Specificity Radiographic Image Interpretation, Computer-Assisted Algorithms Radiography, Thoracic Male Middle Aged Female
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Deep-learning algorithms for the interpretation of chest radiographs to aid in the triage of COVID-19 patients: A multicenter retrospective study.

PloS one Nov 24, 2020
The recent medical applications of deep-learning (DL) algorithms have demonstrated their clinical efficacy in improving speed and accuracy of image interpretation. If the DL algorithm achieves a performance equivalent to that achieved by physicians i...
Female Reproducibility of Results SARS-CoV-2 Aged Retrospective Studies Tomography, X-Ray Computed Republic of Korea Humans Male Data Accuracy COVID-19 Middle Aged Triage Radiography, Thoracic Deep Learning Aged, 80 and over Radiologists Reverse Transcriptase Polymerase Chain Reaction Adult Radiographic Image Interpretation, Computer-Assisted Sensitivity and Specificity
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Exploiting Multiple Optimizers with Transfer Learning Techniques for the Identification of COVID-19 Patients.

Journal of healthcare engineering Nov 23, 2020
Due to the rapid spread of COVID-19 and its induced death worldwide, it is imperative to develop a reliable tool for the early detection of this disease. Chest X-ray is currently accepted to be one of the reliable means for such a detection purpose. ...
Sensitivity and Specificity COVID-19 Humans Lung Databases, Factual Early Diagnosis Machine Learning Radiographic Image Interpretation, Computer-Assisted Reproducibility of Results Radiography, Thoracic Software SARS-CoV-2
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