Machine learning for antimicrobial resistance prediction: current practice, limitations, and clinical perspective
Antimicrobial resistance (AMR) is a global health crisis that poses a great threat to modern
medicine. Effective prevention strategies are urgently required to slow the emergence and …
medicine. Effective prevention strategies are urgently required to slow the emergence and …
“It takes a village”: mechanisms underlying antimicrobial recalcitrance of polymicrobial biofilms
G Orazi, GA O'Toole - Journal of Bacteriology, 2019 - Am Soc Microbiol
Chronic infections are frequently caused by polymicrobial biofilms. Importantly, these
infections are often difficult to treat effectively in part due to the recalcitrance of biofilms to …
infections are often difficult to treat effectively in part due to the recalcitrance of biofilms to …
Molecular architecture of early dissemination and massive second wave of the SARS-CoV-2 virus in a major metropolitan area
We sequenced the genomes of 5,085 severe acute respiratory syndrome coronavirus 2
(SARS-CoV-2) strains causing two coronavirus disease 2019 (COVID-19) disease waves in …
(SARS-CoV-2) strains causing two coronavirus disease 2019 (COVID-19) disease waves in …
Using Machine Learning To Predict Antimicrobial MICs and Associated Genomic Features for Nontyphoidal Salmonella
Nontyphoidal Salmonella species are the leading bacterial cause of foodborne disease in
the United States. Whole-genome sequences and paired antimicrobial susceptibility data …
the United States. Whole-genome sequences and paired antimicrobial susceptibility data …
Applications of machine learning to the problem of antimicrobial resistance: an emerging model for translational research
Antimicrobial resistance (AMR) remains one of the most challenging phenomena of modern
medicine. Machine learning (ML) is a subfield of artificial intelligence that focuses on the …
medicine. Machine learning (ML) is a subfield of artificial intelligence that focuses on the …
Machine learning with random subspace ensembles identifies antimicrobial resistance determinants from pan-genomes of three pathogens
The evolution of antimicrobial resistance (AMR) poses a persistent threat to global public
health. Sequencing efforts have already yielded genome sequences for thousands of …
health. Sequencing efforts have already yielded genome sequences for thousands of …
Genome-scale metabolic models and machine learning reveal genetic determinants of antibiotic resistance in Escherichia coli and unravel the underlying metabolic …
Antimicrobial resistance (AMR) is becoming one of the largest threats to public health
worldwide, with the opportunistic pathogen Escherichia coli playing a major role in the AMR …
worldwide, with the opportunistic pathogen Escherichia coli playing a major role in the AMR …
Genomic features associated with the degree of phenotypic resistance to carbapenems in carbapenem-resistant Klebsiella pneumoniae
Carbapenem-resistant Klebsiella pneumoniae strains cause severe infections that are
difficult to treat. The production of carbapenemases such as the K. pneumoniae …
difficult to treat. The production of carbapenemases such as the K. pneumoniae …
Predicting phenotypic polymyxin resistance in Klebsiella pneumoniae through machine learning analysis of genomic data
Polymyxins are used as treatments of last resort for Gram-negative bacterial infections. Their
increased use has led to concerns about emerging polymyxin resistance (PR). Phenotypic …
increased use has led to concerns about emerging polymyxin resistance (PR). Phenotypic …
The role of artificial intelligence in the battle against antimicrobial-resistant bacteria
Antimicrobial resistance (AMR) in bacteria is a global health crisis due to the rapid
emergence of multidrug-resistant bacteria and the lengthy development of new …
emergence of multidrug-resistant bacteria and the lengthy development of new …