Cargando…
Supervised machine learning in the mass spectrometry laboratory: A tutorial
As the demand for laboratory testing by mass spectrometry increases, so does the need for automated methods for data analysis. Clinical mass spectrometry (MS) data is particularly well-suited for machine learning (ML) methods, which deal nicely with structured and discrete data elements. The alignme...
Autores principales: | Lee, Edward S., Durant, Thomas J.S. |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8692990/ https://www.ncbi.nlm.nih.gov/pubmed/34984411 http://dx.doi.org/10.1016/j.jmsacl.2021.12.001 |
Ejemplares similares
-
Data parsing in mass spectrometry imaging using R Studio and Cardinal: A tutorial
por: Shedlock, Cameron J., et al.
Publicado: (2021) -
Create laboratory business intelligence dashboards for free using R: A tutorial using the flexdashboard package
por: Haymond, Shannon
Publicado: (2021) -
An overview of image registration for aligning mass spectrometry imaging with clinically relevant imaging modalities
por: Balluff, Benjamin, et al.
Publicado: (2021) -
Lipid analysis by ion mobility spectrometry combined with mass spectrometry: A brief update with a perspective on applications in the clinical laboratory
por: Dubland, Joshua A.
Publicado: (2021) -
Network Analysis on Attitudes: A Brief Tutorial
por: Dalege, Jonas, et al.
Publicado: (2017)