AIMC Topic: Tuberculosis, Pulmonary

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Deep Learning to Determine the Activity of Pulmonary Tuberculosis on Chest Radiographs.

Radiology Aug 3, 2021
Background Determining the activity of pulmonary tuberculosis on chest radiographs is difficult. Purpose To develop a deep learning model to identify active pulmonary tuberculosis on chest radiographs. Materials and Methods Chest radiographs were ret...
Humans Retrospective Studies Lung Deep Learning Radiographic Image Interpretation, Computer-Assisted Tuberculosis, Pulmonary Radiography, Thoracic Female Sensitivity and Specificity Male Middle Aged
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Automated detection of Mycobacterium tuberculosis using transfer learning.

Journal of infection in developing countries May 31, 2021
INTRODUCTION: Quantitative analysis of Mycobacterium tuberculosis using microscope is very critical for diagnosing tuberculosis diseases. Microbiologist encounter several challenges which can lead to misdiagnosis. However, there are 3 main challenges...
Mycobacterium tuberculosis Diagnostic Tests, Routine Humans Machine Learning Sensitivity and Specificity Tuberculosis, Pulmonary
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Prediction of the duration needed to achieve culture negativity in patients with active pulmonary tuberculosis using convolutional neural networks and chest radiography.

Respiratory investigation Mar 9, 2021
BACKGROUND: We aimed to predict the duration needed to achieve culture negativity in patients with active pulmonary tuberculosis using convolutional neural networks (CNNs) and chest radiography.
Lung Radiography Tuberculosis, Pulmonary Humans Neural Networks, Computer
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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.
Retrospective Studies Tomography, X-Ray Computed Reproducibility of Results Diagnosis, Computer-Assisted Software COVID-19 Algorithms Databases, Factual Radiography, Thoracic Stochastic Processes Community-Acquired Infections Imaging, Three-Dimensional Pneumonia Tuberculosis, Pulmonary Medical Informatics Humans Neural Networks, Computer
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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 ...
Humans Software Diffusion of Innovation Automation Host-Pathogen Interactions Predictive Value of Tests Radiography, Thoracic Reproducibility of Results Radiographic Image Interpretation, Computer-Assisted Lung Tuberculosis, Pulmonary Diagnosis, Computer-Assisted Mycobacterium tuberculosis Deep Learning
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Chest x-ray analysis with deep learning-based software as a triage test for pulmonary tuberculosis: a prospective study of diagnostic accuracy for culture-confirmed disease.

The Lancet. Digital health Oct 19, 2020
BACKGROUND: Deep learning-based radiological image analysis could facilitate use of chest x-rays as triage tests for pulmonary tuberculosis in resource-limited settings. We sought to determine whether commercially available chest x-ray analysis softw...
Sputum Pakistan Tuberculosis, Pulmonary Mycobacterium tuberculosis Sex Factors X-Rays Body Mass Index Age Factors Triage Radiology Lung Deep Learning HIV Infections Image Processing, Computer-Assisted Humans Software Sensitivity and Specificity Prospective Studies Male Female Young Adult Middle Aged Adult
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Machine Learning-Based Differentiation of Nontuberculous Mycobacteria Lung Disease and Pulmonary Tuberculosis Using CT Images.

BioMed research international Sep 29, 2020
An increasing number of patients infected with nontuberculous mycobacteria (NTM) are observed worldwide. However, it is challenging to identify NTM lung diseases from pulmonary tuberculosis (PTB) due to considerable overlap in classic manifestations ...
Middle Aged Lung Tuberculosis, Pulmonary Image Interpretation, Computer-Assisted Humans Aged Machine Learning Mycobacterium Infections, Nontuberculous Bronchiectasis Adult Tomography, X-Ray Computed Nontuberculous Mycobacteria Sensitivity and Specificity Female Male
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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...
Deep Learning Radiography Tuberculosis, Pulmonary Radiography, Thoracic Humans Algorithms Young Adult Adult Sensitivity and Specificity
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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...
Sensitivity and Specificity Diagnosis, Computer-Assisted Deep Learning Computer Systems Neural Networks, Computer Tuberculosis, Pulmonary Radiography, Thoracic Humans ROC Curve Algorithms False Positive Reactions Thorax Area Under Curve Databases, Factual X-Rays Equipment Design Reproducibility of Results Radiographic Image Interpretation, Computer-Assisted
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Comparison of Xpert MTB/RIF (G4) and Xpert Ultra, including trace readouts, for the diagnosis of pulmonary tuberculosis in a TB and HIV endemic setting.

International journal of infectious diseases : IJID : official publication of the International Society for Infectious Diseases Apr 2, 2020
BACKGROUND: There are limited data about Xpert-Ultra performance in different settings, in HIV-infected persons, in those with a history of previous TB, and with trace readouts.
HIV Infections Real-Time Polymerase Chain Reaction Limit of Detection Sputum Tuberculosis, Pulmonary Mycobacterium tuberculosis Adult Expert Systems Humans Sensitivity and Specificity Male Female Middle Aged Aged Young Adult
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