AIMC Topic: Tuberculosis

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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
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...

Thinking Beyond Disease Silos: Dysregulated Genes Common in Tuberculosis and Lung Cancer as Identified by Systems Biology and Machine Learning.

Omics : a journal of integrative biology
The traditional way of thinking about human diseases across clinical and narrow phenomics silos often masks the underlying shared molecular substrates across human diseases. One Health and planetary health fields particularly address such complexitie...

Machine learning algorithms using national registry data to predict loss to follow-up during tuberculosis treatment.

BMC public health
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...

Enhancing multi-class lung disease classification in chest x-ray images: A hybrid manta-ray foraging volcano eruption algorithm boosted multilayer perceptron neural network approach.

Network (Bristol, England)
One of the most used diagnostic imaging techniques for identifying a variety of lung and bone-related conditions is the chest X-ray. Recent developments in deep learning have demonstrated several successful cases of illness diagnosis from chest X-ray...

Prediction of tuberculosis clusters in the riverine municipalities of the Brazilian Amazon with machine learning.

Revista brasileira de epidemiologia = Brazilian journal of epidemiology
OBJECTIVE: Tuberculosis (TB) is the second most deadly infectious disease globally, posing a significant burden in Brazil and its Amazonian region. This study focused on the "riverine municipalities" and hypothesizes the presence of TB clusters in th...

Enhancing tuberculosis vaccine development: a deconvolution neural network approach for multi-epitope prediction.

Scientific reports
Tuberculosis (TB) a disease caused by Mycobacterium tuberculosis (Mtb) poses a significant threat to human life, and current BCG vaccinations only provide sporadic protection, therefore there is a need for developing efficient vaccines. Numerous immu...

Recent advances in the development of DprE1 inhibitors using AI/CADD approaches.

Drug discovery today
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...

Combining Artificial Intelligence and Simplified Image Processing for the Automatic Detection of Mycobacterium tuberculosis in Acid-fast Stain : A Cross-institute Training and Validation Study.

The American journal of surgical pathology
Tuberculosis (TB) poses a significant health threat in Taiwan, necessitating efficient detection methods. Traditional screening for acid-fast positive bacilli in acid-fast stain is time-consuming and prone to human error due to staining artifacts. To...

TB-DROP: deep learning-based drug resistance prediction of Mycobacterium tuberculosis utilizing whole genome mutations.

BMC genomics
The most widely practiced strategy for constructing the deep learning (DL) prediction model for drug resistance of Mycobacterium tuberculosis (MTB) involves the adoption of ready-made and state-of-the-art architectures usually proposed for non-biolog...