AIMC Topic: Mycobacterium tuberculosis
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A biochemically-interpretable machine learning classifier for microbial GWAS.
Nature communications
May 22, 2020
Current machine learning classifiers have successfully been applied to whole-genome sequencing data to identify genetic determinants of antimicrobial resistance (AMR), but they lack causal interpretation. Here we present a metabolic model-based machi...
Comparison of Xpert MTB/RIF (G4) and Xpert Ultra, including trace readouts, for the diagnosis of pulmonary tuberculosis in a TB and HIV endemic setting.
International journal of infectious diseases : IJID : official publication of the International Society for Infectious Diseases
Apr 2, 2020
BACKGROUND: There are limited data about Xpert-Ultra performance in different settings, in HIV-infected persons, in those with a history of previous TB, and with trace readouts.
Artificial Intelligence and Machine learning based prediction of resistant and susceptible mutations in Mycobacterium tuberculosis.
Scientific reports
Mar 26, 2020
Tuberculosis (TB), an infectious disease caused by Mycobacterium tuberculosis (M.tb), causes highest number of deaths globally for any bacterial disease necessitating novel diagnosis and treatment strategies. High-throughput sequencing methods genera...
Humans
Artificial Intelligence
Machine Learning
Bayes Theorem
Bacterial Proteins
Mutation
Tuberculosis, Multidrug-Resistant
Algorithms
Molecular Docking Simulation
Drug Resistance, Multiple, Bacterial
Polymorphism, Single Nucleotide
Genes, MDR
Molecular Dynamics Simulation
Mycobacterium tuberculosis
Genes, Bacterial
Deep learning, computer-aided radiography reading for tuberculosis: a diagnostic accuracy study from a tertiary hospital in India.
Scientific reports
Jan 14, 2020
In general, chest radiographs (CXR) have high sensitivity and moderate specificity for active pulmonary tuberculosis (PTB) screening when interpreted by human readers. However, they are challenging to scale due to hardware costs and the dearth of pro...
A genetic programming-based approach to identify potential inhibitors of serine protease of .
Future medicinal chemistry
Nov 15, 2019
We applied genetic programming approaches to understand the impact of descriptors on inhibitory effects of serine protease inhibitors of () and the discovery of new inhibitors as drug candidates. The experimental dataset of serine protease inhibit...
ATBdiscrimination: An in Silico Tool for Identification of Active Tuberculosis Disease Based on Routine Blood Test and T-SPOT.TB Detection Results.
Journal of chemical information and modeling
Oct 25, 2019
Tuberculosis remains one of the deadliest infectious diseases worldwide. Only 5-15% of people infected with develop active TB disease (ATB), while others remain latently infected (LTBI) during their lifetime, which has a completely different clinica...
Using artificial intelligence to read chest radiographs for tuberculosis detection: A multi-site evaluation of the diagnostic accuracy of three deep learning systems.
Scientific reports
Oct 18, 2019
Deep learning (DL) neural networks have only recently been employed to interpret chest radiography (CXR) to screen and triage people for pulmonary tuberculosis (TB). No published studies have compared multiple DL systems and populations. We conducted...
SecProMTB: Support Vector Machine-Based Classifier for Secretory Proteins Using Imbalanced Data Sets Applied to Mycobacterium tuberculosis.
Proteomics
Aug 8, 2019
Secretory proteins of Mycobacterium tuberculosis have created more concern, given their dominant immunogenicity and role in pathogenesis. In view of expensive and time-consuming traditional biochemical experiments, an advanced support vector machine ...
Beyond multidrug resistance: Leveraging rare variants with machine and statistical learning models in Mycobacterium tuberculosis resistance prediction.
EBioMedicine
Apr 29, 2019
BACKGROUND: The diagnosis of multidrug resistant and extensively drug resistant tuberculosis is a global health priority. Whole genome sequencing of clinical Mycobacterium tuberculosis isolates promises to circumvent the long wait times and limited s...
Genomics
Computational Biology
Databases, Genetic
Humans
Reproducibility of Results
Cluster Analysis
Models, Statistical
Genetic Variation
Machine Learning
Microbial Sensitivity Tests
Evolution, Molecular
Mycobacterium tuberculosis
Prognosis
ROC Curve
Antitubercular Agents
Genome, Bacterial
Tuberculosis, Multidrug-Resistant
Extensively Drug-Resistant Tuberculosis
An effective and accurate identification system of Mycobacterium tuberculosis using convolution neural networks.
Microscopy research and technique
Feb 11, 2019
Tuberculosis (TB) remains the leading cause of morbidity and mortality from infectious disease in developing countries. The sputum smear microscopy remains the primary diagnostic laboratory test. However, microscopic examination is always time-consum...
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