AIMC Topic: Radiography, Thoracic
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The current status and future of FDA-approved artificial intelligence tools in chest radiology in the United States.
Clinical radiology
Sep 28, 2022
Artificial intelligence (AI) is becoming more widespread within radiology. Capabilities that AI algorithms currently provide include detection, segmentation, classification, and quantification of pathological findings. Artificial intelligence softwar...
Validation study of machine-learning chest radiograph software in primary and emergency medicine.
Clinical radiology
Sep 25, 2022
AIM: To evaluate the performance of a machine learning based algorithm tool for chest radiographs (CXRs), applied to a consecutive cohort of historical clinical cases, in comparison to expert chest radiologists.
Validation of deep learning-based computer-aided detection software use for interpretation of pulmonary abnormalities on chest radiographs and examination of factors that influence readers' performance and final diagnosis.
Japanese journal of radiology
Sep 19, 2022
PURPOSE: To evaluate the performance of a deep learning-based computer-aided detection (CAD) software for detecting pulmonary nodules, masses, and consolidation on chest radiographs (CRs) and to examine the effect of readers' experience and data char...
Deep Learning Detection of Active Pulmonary Tuberculosis at Chest Radiography Matched the Clinical Performance of Radiologists.
Radiology
Sep 6, 2022
Background The World Health Organization (WHO) recommends chest radiography to facilitate tuberculosis (TB) screening. However, chest radiograph interpretation expertise remains limited in many regions. Purpose To develop a deep learning system (DLS)...
Deep Convolutional Neural Network Mechanism Assessment of COVID-19 Severity.
BioMed research international
Aug 23, 2022
As an epidemic, COVID-19's core test instrument still has serious flaws. To improve the present condition, all capabilities and tools available in this field are being used to combat the pandemic. Because of the contagious characteristics of the uniq...
Predicting Patient Demographics From Chest Radiographs With Deep Learning.
Journal of the American College of Radiology : JACR
Aug 11, 2022
BACKGROUND: Deep learning models are increasingly informing medical decision making, for instance, in the detection of acute intracranial hemorrhage and pulmonary embolism. However, many models are trained on medical image databases that poorly repre...
BRAX, Brazilian labeled chest x-ray dataset.
Scientific data
Aug 10, 2022
Chest radiographs allow for the meticulous examination of a patient's chest but demands specialized training for proper interpretation. Automated analysis of medical imaging has become increasingly accessible with the advent of machine learning (ML) ...
Deep Learning-Aided Automated Pneumonia Detection and Classification Using CXR Scans.
Computational intelligence and neuroscience
Aug 4, 2022
The COVID-19 pandemic has caused a worldwide catastrophe and widespread devastation that reeled almost all countries. The pandemic has mounted pressure on the existing healthcare system and caused panic and desperation. The gold testing standard for ...
Explainable emphysema detection on chest radiographs with deep learning.
PloS one
Jul 28, 2022
We propose a deep learning system to automatically detect four explainable emphysema signs on frontal and lateral chest radiographs. Frontal and lateral chest radiographs from 3000 studies were retrospectively collected. Two radiologists annotated th...
Clinically focused multi-cohort benchmarking as a tool for external validation of artificial intelligence algorithm performance in basic chest radiography analysis.
Scientific reports
Jul 27, 2022
Artificial intelligence (AI) algorithms evaluating [supine] chest radiographs ([S]CXRs) have remarkably increased in number recently. Since training and validation are often performed on subsets of the same overall dataset, external validation is man...
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