AIMC Topic: Tuberculosis

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Risk factors for tuberculosis treatment outcomes: a statistical learning-based exploration using the SINAN database with incomplete observations.

BMC medical informatics and decision making
BACKGROUND: Understanding early predictors of treatment outcomes allows better outcome prediction and resource allocation for efficient tuberculosis (TB) management.

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

Scientific reports
Adherence to antiretroviral therapy (ART) is critical for HIV treatment success, yet the impact of tuberculosis preventive therapy (TPT) remains inadequately understood. Using observational data from 4152 HIV patients in Ethiopia (2005-2024), we appl...

Plasma proteomics for biomarker discovery in childhood tuberculosis.

Nature communications
Failure to rapidly diagnose tuberculosis disease (TB) and initiate treatment is a driving factor of TB as a leading cause of death in children. Current TB diagnostic assays have poor performance in children, thus a global priority is the identificati...

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

Scientific reports
With human guidance, computers now use machine learning (ML) in artificial intelligence (AI) to learn from data, detect trends, and make predictions. Software can adapt and improve with new information. Imaging scans leverage pattern recognition to p...

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

BMJ open
INTRODUCTION: Effective health management is critical for patients with tuberculosis (TB), especially given the need for long-term treatment adherence and continuous monitoring. Artificial intelligence (AI)-assisted remote health management services ...

Predictive modelling of air pollution affecting human tuberculosis risk on Mainland China.

Scientific reports
In this study, we investigated the correlation between air pollution indicators and pulmonary tuberculosis (TB) incidence and mortality rates across provincial administrative regions of China from January 2013 to December 2020 to develop predictive m...

Exploring T-cell metabolism in tuberculosis: development of a diagnostic model using metabolic genes.

European journal of medical research
OBJECTIVES: The early diagnosis and immunoregulatory mechanisms of active tuberculosis (ATB) and latent tuberculosis infection (LTBI) remain unclear, and the role of metabolic genes in host-pathogen interactions requires further investigation.

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

Scientific reports
Tuberculosis, a deadly and contagious disease caused by Mycobacterium tuberculosis, remains a significant global public health threat. HIV co-infection significantly increases the risk of active TB recurrence and prolongs medical treatment for tuberc...

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

Scientific reports
Tuberculosis (TB) is a major global health issue, contributing significantly to mortality and morbidity rates worldwide. Socioeconomic, environmental, and healthcare factors significantly impact TB trends. Therefore, we aimed to predict TB and identi...

Tuberculosis detection using few shot learning.

Scientific reports
Tuberculosis (TB), a contagious disease, significantly affects lungs functioning. Amongst multiple detection methodologies, Chest X-ray analysis is considered the most effective methodology. Traditional Deep Learning methodologies have shown good res...