Last Posted: Jan 21, 2025
- Identification of patient demographic, clinical, and SARS-CoV-2 genomic factors associated with severe COVID-19 using supervised machine learning: a retrospective multicenter study.
Kuganya Nirmalarajah et al. BMC Infect Dis 2025 1 (1) 132 - Machine learning reveals the dynamic importance of accessory sequences for Salmonella outbreak clustering.
Chao Chun Liu et al. mBio 2025 1 e0265024 - Using genomic data and machine learning to predict antibiotic resistance: A tutorial paper.
Faye Orcales et al. PLoS Comput Biol 2025 1 (12) e1012579 - Machine learning-based prediction of antibiotic resistance in Mycobacterium tuberculosis clinical isolates from Uganda.
Sandra Ruth Babirye et al. BMC Infect Dis 2024 12 (1) 1391 - Leveraging large-scale Mycobacterium tuberculosis whole genome sequence data to characterise drug-resistant mutations using machine learning and statistical approaches.
Siddharth Sanjay Pruthi et al. Sci Rep 2024 11 (1) 27091 - Enhancing SARS-CoV-2 Lineage Surveillance through the Integration of a Simple and Direct qPCR-Based Protocol Adaptation with Established Machine Learning Algorithms.
Cleber Furtado Aksenen et al. Anal Chem 2024 11 - The Synergy of Machine Learning and Epidemiology in Addressing Carbapenem Resistance: A Comprehensive Review
Sakagianni A, et al. Antibiotics, Oct 21, 2024. - Liquid saliva-based Raman spectroscopy device with on-board machine learning detects COVID-19 infection in real-time.
Katherine J I Ember et al. Analyst 2024 10 - Application of machine learning based genome sequence analysis in pathogen identification.
Yunqiu Gao et al. Front Microbiol 2024 10 1474078 - Machine learning to attribute the source of Campylobacter infections in the United States: A retrospective analysis of national surveillance data.
Ben Pascoe et al. J Infect 2024 9 (5) 106265
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Disclaimer: Articles listed in the Public Health Genomics and Precision Health Knowledge Base are selected by the CDC Office of Public Health Genomics to provide current awareness of the literature and news. Inclusion in the update does not necessarily represent the views of the Centers for Disease Control and Prevention nor does it imply endorsement of the article's methods or findings. CDC and DHHS assume no responsibility for the factual accuracy of the items presented. The selection, omission, or content of items does not imply any endorsement or other position taken by CDC or DHHS. Opinion, findings and conclusions expressed by the original authors of items included in the update, or persons quoted therein, are strictly their own and are in no way meant to represent the opinion or views of CDC or DHHS. References to publications, news sources, and non-CDC Websites are provided solely for informational purposes and do not imply endorsement by CDC or DHHS.