AIMC Topic: Drug Resistance, Microbial
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Highly accurate classification and discovery of microbial protein-coding gene functions using FunGeneTyper: an extensible deep learning framework.
Briefings in bioinformatics
May 23, 2024
High-throughput DNA sequencing technologies decode tremendous amounts of microbial protein-coding gene sequences. However, accurately assigning protein functions to novel gene sequences remain a challenge. To this end, we developed FunGeneTyper, an e...
Enhancing Antibiotic Stewardship: A Machine Learning Approach to Predicting Antibiotic Resistance in Inpatient Care.
AMIA ... Annual Symposium proceedings. AMIA Symposium
Jan 1, 2024
Antibiotics have been crucial in advancing medical treatments, but the growing threat of antibiotic resistance challenges these achievements and emphasizes the need for innovative stewardship strategies. In this study, we developed machine learning m...
Highlights From IDWeek 2023-New Vaccines, Artificial Intelligence, and Antimicrobial Resistance.
JAMA
Dec 5, 2023
Using chronobiology-based second-generation artificial intelligence digital system for overcoming antimicrobial drug resistance in chronic infections.
Annals of medicine
Dec 1, 2023
Antimicrobial resistance results from the widespread use of antimicrobial agents and is a significant obstacle to the effectiveness of these agents. Numerous methods are used to overcome this problem with moderate success. Besides efforts of antimicr...
PLM-ARG: antibiotic resistance gene identification using a pretrained protein language model.
Bioinformatics (Oxford, England)
Nov 1, 2023
MOTIVATION: Antibiotic resistance presents a formidable global challenge to public health and the environment. While considerable endeavors have been dedicated to identify antibiotic resistance genes (ARGs) for assessing the threat of antibiotic resi...
CARD 2023: expanded curation, support for machine learning, and resistome prediction at the Comprehensive Antibiotic Resistance Database.
Nucleic acids research
Jan 6, 2023
The Comprehensive Antibiotic Resistance Database (CARD; card.mcmaster.ca) combines the Antibiotic Resistance Ontology (ARO) with curated AMR gene (ARG) sequences and resistance-conferring mutations to provide an informatics framework for annotation a...
Automated extraction of genes associated with antibiotic resistance from the biomedical literature.
Database : the journal of biological databases and curation
Jan 29, 2022
The detection of bacterial antibiotic resistance phenotypes is important when carrying out clinical decisions for patient treatment. Conventional phenotypic testing involves culturing bacteria which requires a significant amount of time and work. Who...
Predicting Antibiotic Resistance in Hospitalized Patients by Applying Machine Learning to Electronic Medical Records.
Clinical infectious diseases : an official publication of the Infectious Diseases Society of America
Jun 1, 2021
BACKGROUND: Computerized decision support systems are becoming increasingly prevalent with advances in data collection and machine learning (ML) algorithms. However, they are scarcely used for empiric antibiotic therapy. Here, we predict the antibiot...
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