Machine learning for antimicrobial resistance prediction: current practice, limitations, and clinical perspective

JI Kim, F Maguire, KK Tsang, T Gouliouris… - Clinical microbiology …, 2022 - journals.asm.org
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 …

Bacteria exposed to antiviral drugs develop antibiotic cross-resistance and unique resistance profiles

VJ Wallace, EG Sakowski, SP Preheim… - Communications …, 2023 - nature.com
Antiviral drugs are used globally as treatment and prophylaxis for long-term and acute viral
infections. Even though antivirals also have been shown to have off-target effects on …

Predictive modeling of antibiotic eradication therapy success for new-onset Pseudomonas aeruginosa pulmonary infections in children with cystic fibrosis

L Graña-Miraglia, N Morales-Lizcano… - PLoS computational …, 2023 - journals.plos.org
Chronic Pseudomonas aeruginosa (Pa) lung infections are the leading cause of mortality
among cystic fibrosis (CF) patients; therefore, the eradication of new-onset Pa lung …

[HTML][HTML] Genome-Wide Association Study Reveals Host Factors Affecting Conjugation in Escherichia coli

L Van Wonterghem, M De Chiara, G Liti, J Warringer… - Microorganisms, 2022 - mdpi.com
The emergence and dissemination of antibiotic resistance threaten the treatment of common
bacterial infections. Resistance genes are often encoded on conjugative elements, which …

Identification of key drivers of antimicrobial resistance in Enterococcus using machine learning

JI Kim, A Manuele, F Maguire, R Zaheer… - Canadian Journal of …, 2024 - cdnsciencepub.com
With antimicrobial resistance (AMR) rapidly evolving in pathogens, quick and accurate
identification of genetic determinants of phenotypic resistance is essential for improving …

Plasmid permissiveness of wastewater microbiomes can be predicted from 16S rRNA sequences by machine learning

D Moradigaravand, L Li, A Dechesne, J Nesme… - …, 2023 - academic.oup.com
Abstract Motivation Wastewater treatment plants (WWTPs) harbor a dense and diverse
microbial community. They constantly receive antimicrobial residues and resistant strains …

An Automated Machine Learning Framework for Antimicrobial Resistance Prediction Through Transcriptomics

A Alsiyabi, SA Shahid, A Al-Harrasi - bioRxiv, 2024 - biorxiv.org
The emergence of antimicrobial resistance (AMR) poses a global threat of growing concern
to the healthcare system. To mitigate the spread of resistant pathogens, physicians must …

Applications of Artificial Intelligence and Machine Learning in Antimicrobial Resistance Study

A Praveen, N Bartelo, V Soni - … Resistance: Factors to Findings: Omics and …, 2024 - Springer
Microbes possess a natural capacity to resist antimicrobial agents (substances or
compounds that can stop or slow down their growth). Due to bad administration of antibiotics …

Unleashing Genomic Insights with AB Learning: A Self-Supervised Whole-Genome Language Model

B Naidenov - 2023 - search.proquest.com
The language of genetic code embodies a complex grammar and rich syntax of interacting
molecular elements. In this regard, the standard additive marker encoding scheme's inability …