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Mycobacterium Infections, Nontuberculous

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Role of Soluble T-Cell Immunoglobulin Mucin Domain-3 in Differentiating Nontuberculous Mycobacterial Lung Disease from Pulmonary Colonization.

Archivos de bronconeumologia 35312611
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...
Hepatitis A Virus Cellular Receptor 2 Humans Immunoglobulins Ligands Mucins Mycobacterium Infections, Nontuberculous Pneumonia Programmed Cell Death 1 Receptor T-Lymphocytes
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Machine Learning-Based Differentiation of Nontuberculous Mycobacteria Lung Disease and Pulmonary Tuberculosis Using CT Images.

BioMed research international 33062689
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 ...
Adult Aged Bronchiectasis Female Humans Image Interpretation, Computer-Assisted Lung Machine Learning Male Middle Aged Mycobacterium Infections, Nontuberculous Nontuberculous Mycobacteria Sensitivity and Specificity Tomography, X-Ray Computed Tuberculosis, Pulmonary
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Deep Learning-Based Prediction Model Using Radiography in Nontuberculous Mycobacterial Pulmonary Disease.

Chest 35777447
BACKGROUND: Prognostic prediction of nontuberculous mycobacteria pulmonary disease using a deep learning technique has not been attempted.
Deep Learning Humans Lung Diseases Mycobacterium Infections, Nontuberculous Nontuberculous Mycobacteria Radiography Retrospective Studies
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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 36180035
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 Diagnosis, Differential Humans Lung Diseases Mycobacterium Infections, Nontuberculous Nontuberculous Mycobacteria Retrospective Studies Tomography, X-Ray Computed Tuberculosis, Pulmonary
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Discovery of urinary biosignatures for tuberculosis and nontuberculous mycobacteria classification using metabolomics and machine learning.

Scientific reports 38961191
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...
Aged Amino Acids Area Under Curve Biomarkers Diagnosis, Differential Down-Regulation Humans Liquid Chromatography-Mass Spectrometry Machine Learning Male Metabolome Metabolomics Middle Aged Models, Statistical Mycobacterium Infections, Nontuberculous Phenotype Random Forest ROC Curve Tuberculosis Up-Regulation
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A retrospective study differentiating nontuberculous mycobacterial pulmonary disease from pulmonary tuberculosis on computed tomography using radiomics and machine learning algorithms.

Annals of medicine 39283049
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).
Adult Aged Algorithms Diagnosis, Differential Female Humans Machine Learning Male Middle Aged Mycobacterium Infections, Nontuberculous Radiomics Retrospective Studies ROC Curve Support Vector Machine Tomography, X-Ray Computed Tuberculosis, Pulmonary
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Contribution of machine learning for subspecies identification from Mycobacterium abscessus with MALDI-TOF MS in solid and liquid media.

Microbial biotechnology 39257027
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...
Culture Media Humans Machine Learning Mycobacterium abscessus Mycobacterium Infections, Nontuberculous Spectrometry, Mass, Matrix-Assisted Laser Desorption-Ionization
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Multimodal machine learning-based model for differentiating nontuberculous mycobacteria from .

Frontiers in public health 40034169
OBJECTIVE: To develop and evaluate the effectiveness of multimodal machine learning approach for the differentiation of NTM from MTB.
Adult Aged Algorithms Diagnosis, Differential Female Humans Machine Learning Male Middle Aged Mycobacterium Infections, Nontuberculous Mycobacterium tuberculosis Nontuberculous Mycobacteria Retrospective Studies Tomography, X-Ray Computed Tuberculosis
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