Deep multiple instance learning classifies subtissue locations in mass spectrometry images from tissue-level annotations

MOTIVATION: Mass spectrometry imaging (MSI) characterizes the molecular composition of tissues at spatial resolution, and has a strong potential for distinguishing tissue types, or disease states. This can be achieved by supervised classification, which takes as input MSI spectra, and assigns class...

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Detalles Bibliográficos
Autores principales: Guo, Dan, Föll, Melanie Christine, Volkmann, Veronika, Enderle-Ammour, Kathrin, Bronsert, Peter, Schilling, Oliver, Vitek, Olga
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2020
Materias:
Macromolecular Sequence, Structure, and Function
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7355295/
https://www.ncbi.nlm.nih.gov/pubmed/32657378
http://dx.doi.org/10.1093/bioinformatics/btaa436

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7355295/
https://www.ncbi.nlm.nih.gov/pubmed/32657378
http://dx.doi.org/10.1093/bioinformatics/btaa436

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