Trajectories, bifurcations, and pseudo-time in large clinical datasets: applications to myocardial infarction and diabetes data

BACKGROUND: Large observational clinical datasets are becoming increasingly available for mining associations between various disease traits and administered therapy. These datasets can be considered as representations of the landscape of all possible disease conditions, in which a concrete disease...

Descripción completa

Detalles Bibliográficos
Autores principales: Golovenkin, Sergey E, Bac, Jonathan, Chervov, Alexander, Mirkes, Evgeny M, Orlova, Yuliya V, Barillot, Emmanuel, Gorban, Alexander N, Zinovyev, Andrei
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2020
Materias:
Research
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7688475/
https://www.ncbi.nlm.nih.gov/pubmed/33241287
http://dx.doi.org/10.1093/gigascience/giaa128

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7688475/
https://www.ncbi.nlm.nih.gov/pubmed/33241287
http://dx.doi.org/10.1093/gigascience/giaa128

Ejemplares similares