AIMC Topic: Tuberculosis

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Construction of a diagnostic model for tuberculosis based on long non-coding RNA.

Annals of medicine
BACKGROUND: The World Health Organization encourages the development of novel diagnostic tools based on 'non-sputum' samples to meet global goals for tuberculosis (TB) control. We aimed to develop a machine learning-driven model for TB diagnosis, usi...

Smart photonic crystal fiber optical sensor for tuberculosis detection with machine learning integration.

Scientific reports
One of the most common infectious disease-related causes of death globally, particularly in low- and middle-income nations, persists: tuberculosis. At a manifestation of globalization, causes of death keep growing. As it happens, we have developed a ...

A machine learning model and molecular clusters of epigenetic chromatin regulators in tuberculosis based on bioinformatics and clinical samples.

Scientific reports
The role of chromatin regulators (CRs) in mediating epigenetic changes during tuberculosis (TB) infection remains poorly understood. This study aimed to determine the efficacy of CRs in diagnosing TB and characterizing its heterogeneity. GSE83456 dat...

Investigation of tuberculosis incidence and particulate matter concentration in the middle east.

Scientific reports
Air pollution is the fifth and sixth leading risk factor for global mortality and reduced life expectancy. Studies have established a link between atmospheric pollution and the incidence, hospitalization, and mortality rates of pulmonary tuberculosis...

Explainable machine learning for predicting clinical outcomes in HIV/TB co-infection: a comparative retrospective study.

BMC infectious diseases
BACKGROUND: HIV/TB co-infection presents substantial public-health challenges, showing greater treatment-failure and mortality rates than tuberculosis alone. Recent advances in machine learning (ML) provide a robust means of identifying high-risk pat...

Mycobacterium tuberculosis FAS-II pathway targeted integrative deep learning based identification of potential anti-tubercular agents.

Journal of computer-aided molecular design
Mycobacterium tuberculosis (Mtb) continues to be one of the major contributors to the global burden of infectious diseases. Many drugs used in the current treatment regime have fallen prey to the puzzling phenomenon of antimicrobial resistance. Despi...

Development and application of a deep learning-based tuberculosis diagnostic assistance system in remote areas of Northwest China.

Scientific reports
The Kashgar region, located in Northwest China, has a significantly higher incidence of tuberculosis (TB) compared to the national average. Local governments conduct annual TB screening using medical imaging. However, due to a shortage of radiologist...

Artificial intelligence coupled to pharmacometrics modelling to tailor malaria and tuberculosis treatment in Africa.

Nature communications
Africa's vast genetic diversity poses challenges for optimising drug treatments in the continent, which is exacerbated by the fact that drug discovery and development efforts have historically been performed outside Africa. This has led to suboptimal...

Rapid discrimination of and non-tuberculous mycobacteria disease via interpretive machine learning analysis of routine laboratory tests.

BMJ health & care informatics
OBJECTIVES: Rapid discrimination of infections caused by (MTB) and non-tuberculous mycobacteria (NTM) is crucial in clinical settings. Despite overlapping clinical and radiological features, the two require markedly different therapeutic approaches ...