AIMC Topic: Mycobacterium Infections, Nontuberculous
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Multimodal machine learning-based model for differentiating nontuberculous mycobacteria from .
Frontiers in public health
Feb 17, 2025
OBJECTIVE: To develop and evaluate the effectiveness of multimodal machine learning approach for the differentiation of NTM from MTB.
A retrospective study differentiating nontuberculous mycobacterial pulmonary disease from pulmonary tuberculosis on computed tomography using radiomics and machine learning algorithms.
Annals of medicine
Sep 16, 2024
OBJECTIVE: To evaluate the effectiveness of a machine learning based on computed tomography (CT) radiomics to distinguish nontuberculous mycobacterial pulmonary disease (NTM-PD) from pulmonary tuberculosis (PTB).
Discovery of urinary biosignatures for tuberculosis and nontuberculous mycobacteria classification using metabolomics and machine learning.
Scientific reports
Jul 3, 2024
Nontuberculous mycobacteria (NTM) infection diagnosis remains a challenge due to its overlapping clinical symptoms with tuberculosis (TB), leading to inappropriate treatment. Herein, we employed noninvasive metabolic phenotyping coupled with comprehe...
Amino Acids
Random Forest
Tuberculosis
Mycobacterium Infections, Nontuberculous
Down-Regulation
Phenotype
Up-Regulation
Biomarkers
Metabolome
Aged
Metabolomics
Male
Diagnosis, Differential
Models, Statistical
Middle Aged
Area Under Curve
Liquid Chromatography-Mass Spectrometry
ROC Curve
Humans
Machine Learning
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...
Deep Learning-Based Prediction Model Using Radiography in Nontuberculous Mycobacterial Pulmonary Disease.
Chest
Jun 28, 2022
BACKGROUND: Prognostic prediction of nontuberculous mycobacteria pulmonary disease using a deep learning technique has not been attempted.
Role of Soluble T-Cell Immunoglobulin Mucin Domain-3 in Differentiating Nontuberculous Mycobacterial Lung Disease from Pulmonary Colonization.
Archivos de bronconeumologia
Feb 24, 2021
BACKGROUND: Differentiating between nontuberculous mycobacterial lung disease (NTM-LD) and pulmonary NTM colonization (NTM-Col) is difficult. Compared with healthy controls, patients with NTM-LD generally present immune tolerance along with increased...
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 ...
Contribution of machine learning for subspecies identification from Mycobacterium abscessus with MALDI-TOF MS in solid and liquid media.
Microbial biotechnology
Sep 1, 2024
Mycobacterium abscessus (MABS) displays differential subspecies susceptibility to macrolides. Thus, identifying MABS's subspecies (M. abscessus, M. bolletii and M. massiliense) is a clinical necessity for guiding treatment decisions. We aimed to asse...
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