Inferring disease subtypes from clusters in explanation space

Identification of disease subtypes and corresponding biomarkers can substantially improve clinical diagnosis and treatment selection. Discovering these subtypes in noisy, high dimensional biomedical data is often impossible for humans and challenging for machines. We introduce a new approach to faci...

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Detalles Bibliográficos
Autores principales: Schulz, Marc-Andre, Chapman-Rounds, Matt, Verma, Manisha, Bzdok, Danilo, Georgatzis, Konstantinos
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2020
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7393364/
https://www.ncbi.nlm.nih.gov/pubmed/32732917
http://dx.doi.org/10.1038/s41598-020-68858-7

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7393364/
https://www.ncbi.nlm.nih.gov/pubmed/32732917
http://dx.doi.org/10.1038/s41598-020-68858-7

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