Tuberculosis

Distilling knowledge from graph neural networks trained on cell graphs to non-neural student models.

The development and refinement of artificial intelligence (AI) and machine learning algorithms have ...

Pulmonary diseases accurate recognition using adaptive multiscale feature fusion in chest radiography.

Pulmonary disease can severely impair respiratory function and be life-threatening. Accurately recog...

Application of causal forest double machine learning (DML) approach to assess tuberculosis preventive therapy's impact on ART adherence.

Adherence to antiretroviral therapy (ART) is critical for HIV treatment success, yet the impact of t...

Enhancing India's Health Security Efforts Against  : Gaps and Opportunities.

India bears a quarter of the world's tuberculosis (TB) burden. In 2018, the country set an ambitious...

LGD_Net: Capsule network with extreme learning machine for classification of lung diseases using CT scans.

Lung diseases (LGDs) are related to an extensive range of lung disorders, including pneumonia (PNEUM...

A lightweight hybrid DL model for multi-class chest x-ray classification for pulmonary diseases.

Pulmonary diseases have become one of the main reasons for people's health decline, impacting millio...

Quantum dot-infused nanocomposites: revolutionizing diagnostic sensitivity.

Quantum dot-doped nanocomposites (QDNCs) represent an innovative breakthrough in diagnostic medicine...

Evaluating the accuracy of artificial intelligence-powered chest X-ray diagnosis for paediatric pulmonary tuberculosis (EVAL-PAEDTBAID): Study protocol for a multi-centre diagnostic accuracy study.

INTRODUCTION: Diagnosing pulmonary tuberculosis (PTB) in children is challenging owing to paucibacil...

Revisiting the Marcus inverted regime: modulation strategies for photogenerated ultrafast carrier transfer from semiconducting quantum dots to metal oxides.

Ultrafast charge transfer at quantum-dot/metal-oxide (QD-MO) heterojunctions governs the performance...

Letter to the Editor: "Development and Validation of a Deep Learning Ultrasound Radiomics Model for Predicting Drug Resistance in Lymph Node Tuberculosis a Multicenter Study".

Plasma proteomics for biomarker discovery in childhood tuberculosis.

Failure to rapidly diagnose tuberculosis disease (TB) and initiate treatment is a driving factor of ...

Determination of lung cancer exhaled breath biomarkers using machine learning-a new analysis framework.

Exhaled breath samples of lung cancer patients (LC), tuberculosis (TB) patients and asymptomatic con...

A comprehensive machine learning for high throughput Tuberculosis sequence analysis, functional annotation, and visualization.

With human guidance, computers now use machine learning (ML) in artificial intelligence (AI) to lear...

Machine learning-based prediction of antimicrobial resistance and identification of AMR-related SNPs in Mycobacterium tuberculosis.

BACKGROUND: Mycobacterium tuberculosis (MTB) is a human-specific pathogen that primarily infects hum...

Advancing Tuberculosis Screening: The Clinical Potential of Artificial Intelligence-Generated Radiology Reports for Chest Radiographs.

Graph-based vision transformer with sparsity for training on small datasets from scratch.

Vision Transformers (ViTs) have achieved impressive results in large-scale image classification. How...

Exploring tuberculosis patients' preferences for AI-assisted remote health management services in China: a protocol for a discrete choice experiment.

INTRODUCTION: Effective health management is critical for patients with tuberculosis (TB), especiall...

Unlocking potent anti-tuberculosis natural products through structure-activity relationship analysis.

Tuberculosis (TB) remains a world health problem due to the high number of affected individuals, hig...

Advancements in Tuberculosis Diagnostics: An Update.

Tuberculosis (TB) is one of the major life-threatening diseases caused by a single pathogen which ha...

Disease Classification of Pulmonary Xenon Ventilation MRI Using Artificial Intelligence.

RATIONALE AND OBJECTIVES: Hyperpolarized Xenon magnetic resonance imaging (MRI) measures the extent ...

Development and validation of a deep learning ultrasound radiomics model for predicting drug resistance in lymph node tuberculosis a multicenter study.

BACKGROUND: To develop and validate an ensemble machine learning ultrasound radiomics model for pred...