Machine learning-enabled prediction of antimicrobial resistance in foodborne pathogens

B Yun, X Liao, J Feng, T Ding - CyTA-Journal of Food, 2024 - Taylor & Francis
ABSTRACT The World Health Organization (WHO) has identified antimicrobial resistance
(AMR) as one of the top three global dangers to public health. One of the most vital factors …

FEAMR: a database for surveillance of food and environment-associated antimicrobial resistance

M Mishra, P Kadam, B Doshi, J Saravya… - Interdisciplinary Sciences …, 2022 - Springer
The rapid dissemination of antimicrobial resistance (AMR) has emerged as a serious health
problem on an unprecedented global scale. AMR is predicted to kill more than 10 million …

On the Utility of Genomics-Based Methods for Surveillance of Antimicrobial-Resistant Bacteria in the Food Production Continuum

A Cooper - 2021 - repository.library.carleton.ca
Overuse of antimicrobials in medicine and agriculture are believed to be drivers of the
spread of AMR among pathogenic bacteria. Antimicrobial use in agriculture and food …

Silicon versus Superbug: Assessing Machine Learning's Role in the Fight against Antimicrobial Resistance

T Coxe, RK Azad - Antibiotics, 2023 - mdpi.com
In his 1945 Nobel Prize acceptance speech, Sir Alexander Fleming warned of antimicrobial
resistance (AMR) if the necessary precautions were not taken diligently. As the growing …

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

JI Kim, F Maguire, KK Tsang, T Gouliouris… - Clinical microbiology …, 2022 - Am Soc Microbiol
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 …

Enhancing predictions of antimicrobial resistance of pathogens by expanding the potential resistance gene repertoire using a pan-genome-based feature selection …

MR Yang, YW Wu - BMC bioinformatics, 2022 - Springer
Background Predicting which pathogens might exhibit antimicrobial resistance (AMR) based
on genomics data is one of the promising ways to swiftly and precisely identify AMR …

The role of food chain in antimicrobial resistance spread and One Health approach to reduce risks

P Sagar, A Aseem, SK Banjara, S Veleri - International Journal of Food …, 2023 - Elsevier
The incidence of antimicrobial resistance (AMR) is rapidly spreading worldwide. It is
depleting the repertoire of antibiotics in use but the pace of development of new antibiotics is …

Neural network-based predictions of antimicrobial resistance in Salmonella spp. using k-mers counting from whole-genome sequences

CC Barros - bioRxiv, 2021 - biorxiv.org
Artificial intelligence-based predictions have emerged as a friendly and reliable tool for the
surveillance of the antimicrobial resistance (AMR) worldwide. In this regard, genome …

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 …

[HTML][HTML] Predicting antimicrobial resistance in E. coli with discriminative position fused deep learning classifier

C Jin, C Jia, W Hu, H Xu, Y Shen, M Yue - Computational and Structural …, 2024 - Elsevier
Escherichia coli (E. coli) has become a particular concern due to the increasing incidence of
antimicrobial resistance (AMR) observed worldwide. Using machine learning (ML) to predict …