AIMC Topic: Radiography, Thoracic
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Deep learning-based automated detection algorithm for active pulmonary tuberculosis on chest radiographs: diagnostic performance in systematic screening of asymptomatic individuals.
European radiology
Aug 28, 2020
OBJECTIVES: Performance of deep learning-based automated detection (DLAD) algorithms in systematic screening for active pulmonary tuberculosis is unknown. We aimed to validate DLAD algorithm for detection of active pulmonary tuberculosis and any radi...
Computer-Aided System for the Detection of Multicategory Pulmonary Tuberculosis in Radiographs.
Journal of healthcare engineering
Aug 24, 2020
The early screening and diagnosis of tuberculosis plays an important role in the control and treatment of tuberculosis infections. In this paper, an integrated computer-aided system based on deep learning is proposed for the detection of multiple cat...
Computer Systems
Thorax
ROC Curve
X-Rays
Reproducibility of Results
Area Under Curve
Sensitivity and Specificity
Humans
Radiographic Image Interpretation, Computer-Assisted
Equipment Design
Diagnosis, Computer-Assisted
Neural Networks, Computer
Deep Learning
Tuberculosis, Pulmonary
Algorithms
Databases, Factual
False Positive Reactions
Radiography, Thoracic
Using imaging to combat a pandemic: rationale for developing the UK National COVID-19 Chest Imaging Database.
The European respiratory journal
Aug 13, 2020
https://bit.ly/3eQeuha
Comparing different deep learning architectures for classification of chest radiographs.
Scientific reports
Aug 12, 2020
Chest radiographs are among the most frequently acquired images in radiology and are often the subject of computer vision research. However, most of the models used to classify chest radiographs are derived from openly available deep neural networks,...
Artificial Intelligence Solutions for Analysis of X-ray Images.
Canadian Association of Radiologists journal = Journal l'Association canadienne des radiologistes
Aug 6, 2020
Artificial intelligence (AI) presents a key opportunity for radiologists to improve quality of care and enhance the value of radiology in patient care and population health. The potential opportunity of AI to aid in triage and interpretation of conve...
Extraction of radiographic findings from unstructured thoracoabdominal computed tomography reports using convolutional neural network based natural language processing.
PloS one
Jul 30, 2020
BACKGROUND: Heart failure (HF) is a major cause of morbidity and mortality. However, much of the clinical data is unstructured in the form of radiology reports, while the process of data collection and curation is arduous and time-consuming.
Deep-COVID: Predicting COVID-19 from chest X-ray images using deep transfer learning.
Medical image analysis
Jul 21, 2020
The COVID-19 pandemic is causing a major outbreak in more than 150 countries around the world, having a severe impact on the health and life of many people globally. One of the crucial step in fighting COVID-19 is the ability to detect the infected p...
Deep Learning
Diagnosis, Differential
Predictive Value of Tests
Data Interpretation, Statistical
Pandemics
Radiographic Image Interpretation, Computer-Assisted
Humans
Betacoronavirus
COVID-19
Coronavirus Infections
Neural Networks, Computer
SARS-CoV-2
Datasets as Topic
Pneumonia, Viral
Sensitivity and Specificity
Radiography, Thoracic
Deep Learning-based Automatic Detection Algorithm for Reducing Overlooked Lung Cancers on Chest Radiographs.
Radiology
Jul 21, 2020
Background It is uncertain whether a deep learning-based automatic detection algorithm (DLAD) for identifying malignant nodules on chest radiographs will help diagnose lung cancers. Purpose To evaluate the efficacy of using a DLAD in observer perform...
Diagnosing Heart Failure from Chest X-Ray Images Using Deep Learning.
International heart journal
Jul 18, 2020
The development of deep learning technology has enabled machines to achieve high-level accuracy in interpreting medical images. While many previous studies have examined the detection of pulmonary nodules in chest X-rays using deep learning, the appl...
Implementation of a Deep Learning-Based Computer-Aided Detection System for the Interpretation of Chest Radiographs in Patients Suspected for COVID-19.
Korean journal of radiology
Jul 17, 2020
OBJECTIVE: To describe the experience of implementing a deep learning-based computer-aided detection (CAD) system for the interpretation of chest X-ray radiographs (CXR) of suspected coronavirus disease (COVID-19) patients and investigate the diagnos...
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