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Drug Resistance, Bacterial

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Integrating MALDI-TOF Mass Spectrometry with Machine Learning Techniques for Rapid Antimicrobial Resistance Screening of Foodborne Bacterial Pathogens.

Methods in molecular biology (Clifton, N.J.)
Although MALDI-TOF mass spectrometry (MS) is considered as the gold standard for rapid and cost-effective identification of microorganisms in routine laboratory practices, its capability for antimicrobial resistance (AMR) detection has received limit...

Prediction of Antibiotic Susceptibility in E. coli Isolates Using Machine Learning.

Studies in health technology and informatics
Antimicrobial resistance (AMR) poses a significant global health threat, resulting in 4.96 million deaths in 2019, with projections reaching 10 million by 2050. This resistance, primarily due to the overuse of antibiotics, complicates the treatment o...

Leveraging Graph Neural Networks for MIC Prediction in Antimicrobial Resistance Studies.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Antimicrobial resistance (AMR) poses a significant challenge in healthcare and public health, with organisms such as nontyphoidal Salmonella leading the way due to their escalating resistance to antimicrobial agents. This situation severely complicat...

Scalable de novo classification of antibiotic resistance of Mycobacterium tuberculosis.

Bioinformatics (Oxford, England)
MOTIVATION: World Health Organization estimates that there were over 10 million cases of tuberculosis (TB) worldwide in 2019, resulting in over 1.4 million deaths, with a worrisome increasing trend yearly. The disease is caused by Mycobacterium tuber...

Machine learning-based antibiotic resistance prediction models: An updated systematic review and meta-analysis.

Technology and health care : official journal of the European Society for Engineering and Medicine
BACKGROUND: The widespread use of antibiotics has led to a gradual adaptation of bacteria to these drugs, diminishing the effectiveness of treatments.

Personal Data for Public Benefit: The Regulatory Determinants of Social Licence for Technologically Enhanced Antimicrobial Resistance Surveillance.

Journal of law and medicine
Technologically enhanced surveillance systems have been proposed for the task of monitoring and responding to antimicrobial resistance (AMR) in both human, animal and environmental contexts. The use of these systems is in their infancy, although the ...

Evaluation of Antimicrobial Susceptibility Profile in Salmonella Typhi and Salmonella Paratyphi A: Presenting the Current Scenario in India and Strategy for Future Management.

The Journal of infectious diseases
BACKGROUND: Systematic studies to estimate the disease burden of typhoid and paratyphoid in India are limited. Therefore, a multicenter study on the Surveillance of Enteric Fever in India was carried out to estimate the incidence, clinical presentati...

A machine learning framework to predict antibiotic resistance traits and yet unknown genes underlying resistance to specific antibiotics in bacterial strains.

Briefings in bioinformatics
Recently, the frequency of observing bacterial strains without known genetic components underlying phenotypic resistance to antibiotics has increased. There are several strains of bacteria lacking known resistance genes; however, they demonstrate res...

Deep-ABPpred: identifying antibacterial peptides in protein sequences using bidirectional LSTM with word2vec.

Briefings in bioinformatics
The overuse of antibiotics has led to emergence of antimicrobial resistance, and as a result, antibacterial peptides (ABPs) are receiving significant attention as an alternative. Identification of effective ABPs in lab from natural sources is a cost-...

Prediction of prokaryotic transposases from protein features with machine learning approaches.

Microbial genomics
Identification of prokaryotic transposases (Tnps) not only gives insight into the spread of antibiotic resistance and virulence but the process of DNA movement. This study aimed to develop a classifier for predicting Tnps in bacteria and archaea usin...