AIMC Topic: Tuberculosis
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Identification of diagnostic biomarkers and molecular subtype analysis associated with m6A in Tuberculosis immunopathology using machine learning.
Scientific reports
Dec 2, 2024
Tuberculosis (TB), ranking just below COVID-19 in global mortality, is a highly complex infectious disease involving intricate immunological molecules, diverse signaling pathways, and multifaceted immune processes. N6-methyladenosine (m6A), a critica...
Integrated machine learning and physics-based methods assisted de novo design of Fatty Acyl-CoA synthase inhibitors.
Expert opinion on drug discovery
Nov 25, 2024
BACKGROUND: Tuberculosis is an infectious disease that has become endemic worldwide. The causative bacteria (Mtb) is targeted via several exciting drug targets. One newly discovered target is the Fatty Acyl-CoA synthase, which plays a significant ro...
A comprehensive study on tuberculosis prediction models: Integrating machine learning into epidemiological analysis.
Journal of theoretical biology
Nov 13, 2024
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)
Oct 11, 2024
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...
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
Sep 14, 2024
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...
Lite-YOLOv8: a more lightweight algorithm for Tubercle Bacilli detection.
Medical & biological engineering & computing
Sep 12, 2024
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...
Neural Networks Based Smart E-Health Application for the Prediction of Tuberculosis Using Serverless Computing.
IEEE journal of biomedical and health informatics
Sep 5, 2024
The convergence of the Internet of Things (IoT) with e-health records is creating a new era of advancements in the diagnosis and treatment of disease, which is reshaping the modern landscape of healthcare. In this paper, we propose a neural networks-...
Fuzzy lattices assisted EJAYA Q-learning for automated pulmonary diseases classification.
Biomedical physics & engineering express
Sep 3, 2024
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 comparative analysis of classical and machine learning methods for forecasting TB/HIV co-infection.
Scientific reports
Aug 16, 2024
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...
Prediction of Mycobacterium tuberculosis cell wall permeability using machine learning methods.
Molecular diversity
Aug 12, 2024
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...
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