Machine learning to improve the interpretation of intercalating dye-based quantitative PCR results

This study aimed to evaluate the contribution of Machine Learning (ML) approach in the interpretation of intercalating dye-based quantitative PCR (IDqPCR) signals applied to the diagnosis of mucormycosis. The ML-based classification approach was applied to 734 results of IDqPCR categorized as positi...

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Detalles Bibliográficos
Autores principales: Godmer, A., Bigot, J., Giai Gianetto, Q., Benzerara, Y., Veziris, N., Aubry, A., Guitard, J., Hennequin, C.
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/PMC9525288/
https://www.ncbi.nlm.nih.gov/pubmed/36180590
http://dx.doi.org/10.1038/s41598-022-21010-z

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9525288/
https://www.ncbi.nlm.nih.gov/pubmed/36180590
http://dx.doi.org/10.1038/s41598-022-21010-z

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