Non-negative tensor factorization workflow for time series biomedical data

Non-negative tensor factorization (NTF) enables the extraction of a small number of latent components from high-dimensional biomedical data. However, NTF requires many steps, which is a hurdle to implementation. Here, we provide a protocol for TensorLyCV, an easy to run and reproducible NTF analysis...

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Detalles Bibliográficos
Autores principales: Tsuyuzaki, Koki, Yoshida, Naoki, Ishikawa, Tetsuo, Goshima, Yuki, Kawakami, Eiryo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2023
Materias:
Protocol
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10511860/
https://www.ncbi.nlm.nih.gov/pubmed/37421614
http://dx.doi.org/10.1016/j.xpro.2023.102318

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10511860/
https://www.ncbi.nlm.nih.gov/pubmed/37421614
http://dx.doi.org/10.1016/j.xpro.2023.102318

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