Treatment selection using prototyping in latent-space with application to depression treatment
Machine-assisted treatment selection commonly follows one of two paradigms: a fully personalized paradigm which ignores any possible clustering of patients; or a sub-grouping paradigm which ignores personal differences within the identified groups. While both paradigms have shown promising results,...
Guardado en:
Autores principales: | Akiva Kleinerman, Ariel Rosenfeld, David Benrimoh, Robert Fratila, Caitrin Armstrong, Joseph Mehltretter, Eliyahu Shneider, Amit Yaniv-Rosenfeld, Jordan Karp, Charles F. Reynolds, Gustavo Turecki, Adam Kapelner |
---|---|
Formato: | article |
Lenguaje: | EN |
Publicado: |
Public Library of Science (PLoS)
2021
|
Materias: | |
Acceso en línea: | https://doaj.org/article/340d8807035c463b98f66ee3e0a54178 |
Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Ejemplares similares
-
Treatment selection using prototyping in latent-space with application to depression treatment.
por: Akiva Kleinerman, et al.
Publicado: (2021) -
A Latent Heat Storage System for Low-Temperature Applications: From Materials Selection to Prototype Performances
por: Didier Haillot, et al.
Publicado: (2021) -
EEG p-adic quantum potential accurately identifies depression, schizophrenia and cognitive decline.
por: Oded Shor, et al.
Publicado: (2021) -
Virtual and physical prototyping
Publicado: (2006) -
Rapid prototyping journal
Publicado: (1995)