AIMC Topic: Tuberculosis

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Machine learning identifies MiRNA biomarkers and immune mechanisms in active tuberculosis.

Scientific reports
Tuberculosis (TB), caused by Mycobacterium tuberculosis (Mtb), remains a major global public health threat. The rising prevalence of HIV/TB co-infection and multidrug-resistant tuberculosis (MDR-TB) has further intensified this challenge. This study ...

Discovering Biomarkers for Asymptomatic Tuberculosis via Olink Proteomics and Machine Learning.

Journal of proteome research
The diagnosis of asymptomatic tuberculosis (TB) remains challenging due to an early disease stage. This study aimed to identify and validate plasma biomarkers for asymptomatic TB by integrating the Olink proteomics with multiple machine learning algo...

[New methods of tuberculosis diagnostics].

Deutsche medizinische Wochenschrift (1946)
Tuberculosis remains the leading cause of death by a single infectious agent worldwide, with over 10 million cases annually. Despite global efforts, delayed or missed diagnoses continue to fuel transmission and mortality, particularly in resource-lim...

Preferences of Patients With Tuberculosis for AI-Assisted Remote Health Management: Discrete Choice Experiment.

Journal of medical Internet research
BACKGROUND: Tuberculosis remains a major global public health challenge, especially in low-resource settings where long-term treatment adherence and regular follow-up are critical. The integration of artificial intelligence (AI) into remote health ma...

Gaussian process modelling of infectious diseases using the Greta software package and GPUs.

Journal of theoretical biology
Gaussian process are a widely-used statistical tool for conducting non-parametric inference in applied sciences, with many computational packages available to fit to data and predict future observations. We study the use of the Greta software for Bay...

Lung and abdominal ultrasound accuracy for tuberculosis: An Indian prospective cohort study.

PloS one
BACKGROUND: Tuberculosis (TB) diagnosis remains a challenge, particularly in low-resource settings. Point-of-care ultrasound (POCUS) has shown promise, but most studies focus on HIV-infected populations. In the case of TB, data on lung ultrasound (LU...

Inflammation and B cell activation define a plasma proteome signature predicting tuberculosis in people with HIV.

mBio
Improved biomarkers for predicting progression to active tuberculosis (TB) are urgently needed, especially in people with HIV, who are at elevated risk. We used high-throughput plasma proteomics and machine learning to identify signatures associated ...

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...