AIMC Topic: Antitubercular Agents
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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...
Quantitative drug susceptibility testing for Mycobacterium tuberculosis using unassembled sequencing data and machine learning.
PLoS computational biology
Aug 5, 2024
There remains a clinical need for better approaches to rapid drug susceptibility testing in view of the increasing burden of multidrug resistant tuberculosis. Binary susceptibility phenotypes only capture changes in minimum inhibitory concentration w...
Machine learning investigation of tuberculosis with medicine immunity impact.
Diagnostic microbiology and infectious disease
Aug 4, 2024
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...
Machine Learning Approach in Dosage Individualization of Isoniazid for Tuberculosis.
Clinical pharmacokinetics
Jul 11, 2024
INTRODUCTION: Isoniazid is a first-line antituberculosis agent with high variability, which would profit from individualized dosing. Concentrations of isoniazid at 2 h (C), as an indicator of safety and efficacy, are important for optimizing therapy.
Rapid, antibiotic incubation-free determination of tuberculosis drug resistance using machine learning and Raman spectroscopy.
Proceedings of the National Academy of Sciences of the United States of America
Jun 11, 2024
Tuberculosis (TB) is the world's deadliest infectious disease, with over 1.5 million deaths and 10 million new cases reported anually. The causative organism (Mtb) can take nearly 40 d to culture, a required step to determine the pathogen's antibiot...
Artificial intelligence-based radiographic extent analysis to predict tuberculosis treatment outcomes: a multicenter cohort study.
Scientific reports
Jun 7, 2024
Predicting outcomes in pulmonary tuberculosis is challenging despite effective treatments. This study aimed to identify factors influencing treatment success and culture conversion, focusing on artificial intelligence (AI)-based chest X-ray analysis ...
Machine learning algorithms using national registry data to predict loss to follow-up during tuberculosis treatment.
BMC public health
May 23, 2024
BACKGROUND: Identifying patients at increased risk of loss to follow-up (LTFU) is key to developing strategies to optimize the clinical management of tuberculosis (TB). The use of national registry data in prediction models may be a useful tool to in...
Recent advances in the development of DprE1 inhibitors using AI/CADD approaches.
Drug discovery today
Apr 25, 2024
Tuberculosis (TB) is a global lethal disease caused by Mycobacterium tuberculosis (Mtb). The flavoenzyme decaprenylphosphoryl-β-d-ribose 2'-oxidase (DprE1) plays a crucial part in the biosynthesis of lipoarabinomannan and arabinogalactan for the cell...
Clinical utilization of artificial intelligence in predicting therapeutic efficacy in pulmonary tuberculosis.
Journal of infection and public health
Feb 23, 2024
Traditional methods for monitoring pulmonary tuberculosis (PTB) treatment efficacy lack sensitivity, prompting the exploration of artificial intelligence (AI) to enhance monitoring. This review investigates the application of AI in monitoring anti-tu...
Machine learning assisted methods for the identification of low toxicity inhibitors of Enoyl-Acyl Carrier Protein Reductase (InhA).
Computational biology and chemistry
Feb 20, 2024
Tuberculosis (TB) is one of the life-threatening infectious diseases with prehistoric origins and occurs in almost all habitable parts of the world. TB mainly affects the lungs, and its etiological agent is Mycobacterium tuberculosis (Mtb). In 2022, ...
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