Verifying explainability of a deep learning tissue classifier trained on RNA-seq data

For complex machine learning (ML) algorithms to gain widespread acceptance in decision making, we must be able to identify the features driving the predictions. Explainability models allow transparency of ML algorithms, however their reliability within high-dimensional data is unclear. To test the r...

Descripción completa

Detalles Bibliográficos
Autores principales: Yap, Melvyn, Johnston, Rebecca L., Foley, Helena, MacDonald, Samual, Kondrashova, Olga, Tran, Khoa A., Nones, Katia, Koufariotis, Lambros T., Bean, Cameron, Pearson, John V., Trzaskowski, Maciej, Waddell, Nicola
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2021
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7846764/
https://www.ncbi.nlm.nih.gov/pubmed/33514769
http://dx.doi.org/10.1038/s41598-021-81773-9

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7846764/
https://www.ncbi.nlm.nih.gov/pubmed/33514769
http://dx.doi.org/10.1038/s41598-021-81773-9

Ejemplares similares