Distance-Metric Learning for Personalized Survival Analysis

Personalized time-to-event or survival prediction with right-censored outcomes is a pervasive challenge in healthcare research. Although various supervised machine learning methods, such as random survival forests or neural networks, have been adapted to handle such outcomes effectively, they do not...

Descripción completa

Detalles Bibliográficos
Autores principales: Galetzka, Wolfgang, Kowall, Bernd, Jusi, Cynthia, Huessler, Eva-Maria, Stang, Andreas
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10606222/
https://www.ncbi.nlm.nih.gov/pubmed/37895525
http://dx.doi.org/10.3390/e25101404

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10606222/
https://www.ncbi.nlm.nih.gov/pubmed/37895525
http://dx.doi.org/10.3390/e25101404

Ejemplares similares