Biomarker selection and a prospective metabolite-based machine learning diagnostic for lyme disease

We provide a pipeline for data preprocessing, biomarker selection, and classification of liquid chromatography–mass spectrometry (LCMS) serum samples to generate a prospective diagnostic test for Lyme disease. We utilize tools of machine learning (ML), e.g., sparse support vector machines (SSVM), it...

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Detalles Bibliográficos
Autores principales: Kehoe, Eric R., Fitzgerald, Bryna L., Graham, Barbara, Islam, M. Nurul, Sharma, Kartikay, Wormser, Gary P., Belisle, John T., Kirby, Michael J.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8795431/
https://www.ncbi.nlm.nih.gov/pubmed/35087163
http://dx.doi.org/10.1038/s41598-022-05451-0

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8795431/
https://www.ncbi.nlm.nih.gov/pubmed/35087163
http://dx.doi.org/10.1038/s41598-022-05451-0

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