Pulmonology

Tuberculosis

Latest AI and machine learning research in tuberculosis for healthcare professionals.

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Deep learning-based framework for Mycobacterium tuberculosis bacterial growth detection for antimicrobial susceptibility testing.

Tuberculosis (TB) kills more people annually than any other pathogen. Resistance is an ever-increasi...

Bidirectional Phosphorescent Neuroplasticity for All-Optical Neurovision.

All-optical neuromorphics that can capture, process, and output photonic signals are in prospect to ...

A Hybrid Transformer Architecture with a Quantized Self-Attention Mechanism Applied to Molecular Generation.

The success of the self-attention mechanism in classical machine learning models has inspired the de...

Artificial Intelligence-augmented public health interventions in India.

The adoption and scaling of technology in public health settings in the Global South have traditiona...

Behavior recognition technology based on deep learning used in pediatric behavioral audiometry.

This study aims to explore the feasibility and accuracy of deep learning-based pediatric behavioral ...

A comparative study on TB incidence and HIVTB coinfection using machine learning models on WHO global TB dataset.

Tuberculosis, a deadly and contagious disease caused by Mycobacterium tuberculosis, remains a signif...

Utilizing artificial intelligence to predict and analyze socioeconomic, environmental, and healthcare factors driving tuberculosis globally.

Tuberculosis (TB) is a major global health issue, contributing significantly to mortality and morbid...

Tuberculosis detection using few shot learning.

Tuberculosis (TB), a contagious disease, significantly affects lungs functioning. Amongst multiple d...

Subtractive genomics approach: A guide to unveiling therapeutic targets across pathogens.

Subtractive genomics is an adaptable bioinformatics technique that is used to identify potential the...

Deep Gated Neural Network With Self-Attention Mechanism for Survival Analysis.

Survival analysis is commonly used to model the time distributions of the first occurrences of event...

Performance of Computer-Aided Detection Software in Tuberculosis Case Finding in Township Health Centers in China.

BACKGROUND: Computer-aided detection (CAD) software has been introduced to automatically interpret d...

A Deep-Learning Empowered, Real-Time Processing Platform of fNIRS/DOT for Brain Computer Interfaces and Neurofeedback.

Brain-Computer Interfaces (BCI) and Neurofeedback (NFB) approaches, which both rely on real-time mon...

Comparing discriminatory behavior against AI and humans.

Although discrimination is typically believed to occur from well-defined categories like ethnicity, ...

Enhanced diagnosis of multi-drug-resistant microbes using group association modeling and machine learning.

New solutions are needed to detect genotype-phenotype associations involved in microbial drug resist...

Enhanced tuberculosis detection using Vision Transformers and explainable AI with a Grad-CAM approach on chest X-rays.

Tuberculosis (TB), caused by Mycobacterium tuberculosis, remains a leading global health challenge, ...

Early differential diagnosis models of Talaromycosis and Tuberculosis in HIV-negative hosts using clinical data and machine learning.

BACKGROUND: Talaromyces marneffei is an emerging pathogen, and the number of infections in HIV-negat...

Diagnostic Performance of Artificial Intelligence-Based Methods for Tuberculosis Detection: Systematic Review.

BACKGROUND: Tuberculosis (TB) remains a significant health concern, contributing to the highest mort...

Tuberculosis of the central nervous system: current concepts in diagnosis and treatment.

PURPOSE OF REVIEW: The outcome of central nervous system (CNS) tuberculosis has shown little improve...

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