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Tuberculosis

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Regional and National Trends in Tuberculosis Research in South Asian Association for Regional Cooperation Countries: Post-COVID-19 Pandemic Machine Learning Factorial Analysis.

International journal of mycobacteriology
BACKGROUND: The number of tuberculosis (TB)-related morbidities and mortalities is still high in the South-east Asian region. This study was performed to characterize and visualize the post-coronavirus disease 2019 (COVID-19) TB research in South Asi...

Developing an AI-Assisted Platform to Support Tuberculosis Care Delivery.

Studies in health technology and informatics
Artificial Intelligence (AI) has the potential to "bridge the gap" between healthcare provider and patient needs in low-resource settings to deliver timely, personalized, and empathetic care to individuals with active tuberculosis.

A comparative analysis of classical and machine learning methods for forecasting TB/HIV co-infection.

Scientific reports
TB/HIV coinfection poses a complex public health challenge. Accurate forecasting of future trends is essential for efficient resource allocation and intervention strategy development. This study compares classical statistical and machine learning mod...

Machine learning investigation of tuberculosis with medicine immunity impact.

Diagnostic microbiology and infectious disease
Tuberculosis (T.B.) remains a prominent global cause of health challenges and death, exacerbated by drug-resistant strains such as multidrug-resistant tuberculosis MDR-TB and extensively drug-resistant tuberculosis XDR-TB. For an effective disease ma...

Prediction of Mycobacterium tuberculosis cell wall permeability using machine learning methods.

Molecular diversity
Tuberculosis (TB) caused by the bacteria Mycobacterium tuberculosis (M. tb), continues to pose a significant worldwide health threat. The advent of drug-resistant strains of the disease highlights the critical need for novel treatments. The unique ce...

Lite-YOLOv8: a more lightweight algorithm for Tubercle Bacilli detection.

Medical & biological engineering & computing
Deep learning is a transformative force in the medical field and it has made significant progress as a pivotal alternative to conventional manual testing methods. Detection of Tubercle Bacilli in sputum samples is faced with the problems of complex b...

Fuzzy lattices assisted EJAYA Q-learning for automated pulmonary diseases classification.

Biomedical physics & engineering express
This work proposes a novel technique called Enhanced JAYA (EJAYA) assisted Q-Learning for the classification of pulmonary diseases, such as pneumonia and tuberculosis (TB) sub-classes using chest x-ray images. The work introduces Fuzzy lattices forma...

A comprehensive study on tuberculosis prediction models: Integrating machine learning into epidemiological analysis.

Journal of theoretical biology
Tuberculosis (TB), the second leading infectious killer globally, claimed the lives of 1.3 million individuals in 2022, after COVID-19, surpassing the toll of HIV and AIDS. With an estimated 10.6 million new TB cases worldwide in 2022, the gravity of...

Combining bioinformatics and machine learning to identify diagnostic biomarkers of TB associated with immune cell infiltration.

Tuberculosis (Edinburgh, Scotland)
OBJECTIVE: The asymptomatic nature of tuberculosis (TB) during its latent phase, combined with limitations in current diagnostic methods, makes accurate diagnosis challenging. This study aims to identify TB diagnostic biomarkers by integrating gene e...