AIMC Topic: Tuberculosis, Pulmonary
Clear Filters Showing 21 to 30 of 77 articles
Clinical utilization of artificial intelligence in predicting therapeutic efficacy in pulmonary tuberculosis.
Journal of infection and public health
Feb 23, 2024
Traditional methods for monitoring pulmonary tuberculosis (PTB) treatment efficacy lack sensitivity, prompting the exploration of artificial intelligence (AI) to enhance monitoring. This review investigates the application of AI in monitoring anti-tu...
Application of artificial intelligence in diagnosis of pulmonary tuberculosis.
Chinese medical journal
Feb 19, 2024
Distinguishing infectivity in patients with pulmonary tuberculosis using deep learning.
Frontiers in public health
Nov 27, 2023
INTRODUCTION: This study aimed to develop and assess a deep-learning model based on CT images for distinguishing infectivity in patients with pulmonary tuberculosis (PTB).
Effect of multimodal diagnostic approach using deep learning-based automated detection algorithm for active pulmonary tuberculosis.
Scientific reports
Nov 13, 2023
In this study, we developed a model to predict culture test results for pulmonary tuberculosis (PTB) with a customized multimodal approach and evaluated its performance in different clinical settings. Moreover, we investigated potential performance i...
A systematic review and repeatability study on the use of deep learning for classifying and detecting tuberculosis bacilli in microscopic images.
Progress in biophysics and molecular biology
Apr 5, 2023
Tuberculosis (TB) is among the leading causes of death worldwide from a single infectious agent. This disease usually affects the lungs (pulmonary TB) and can be cured in most cases with a quick diagnosis and proper treatment. Microscopic sputum smea...
Identification of Active Pulmonary Tuberculosis Among Patients With Positive Interferon-Gamma Release Assay Results: Value of a Deep Learning-based Computer-aided Detection System in Different Scenarios of Implementation.
Journal of thoracic imaging
Feb 3, 2023
PURPOSE: To evaluate the accuracy of a deep learning-based computer-aided detection (CAD) system in identifying active pulmonary tuberculosis on chest radiographs (CRs) of patients with positive interferon-gamma release assay (IGRA) results in differ...
Deep learning classification of active tuberculosis lung zones wise manifestations using chest X-rays: a multi label approach.
Scientific reports
Jan 17, 2023
Chest X-rays are the most economically viable diagnostic imaging test for active pulmonary tuberculosis screening despite the high sensitivity and low specificity when interpreted by clinicians or radiologists. Computer aided detection (CAD) algorith...
Deep learning-based harmonization of CT reconstruction kernels towards improved clinical task performance.
European radiology
Nov 10, 2022
OBJECTIVES: To develop a deep learning-based harmonization framework, assessing whether it can improve performance of radiomics models given different kernels in different clinical tasks and additionally generalize to mitigate the effects of new/unob...
T-SPOT with CT image analysis based on deep learning for early differential diagnosis of nontuberculous mycobacteria pulmonary disease and pulmonary tuberculosis.
International journal of infectious diseases : IJID : official publication of the International Society for Infectious Diseases
Sep 28, 2022
OBJECTIVES: This study aimed to establish a diagnostic algorithm combining T-SPOT with computed tomography image analysis based on deep learning (DL) for early differential diagnosis of nontuberculous mycobacteria pulmonary disease (NTM-PD) and pulmo...
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