[Formula: see text] : deep learning-based radiomics for the time-to-event outcome prediction in lung cancer

Hand-crafted radiomics has been used for developing models in order to predict time-to-event clinical outcomes in patients with lung cancer. Hand-crafted features, however, are pre-defined and extracted without taking the desired target into account. Furthermore, accurate segmentation of the tumor i...

Descripción completa

Detalles Bibliográficos
Autores principales: Afshar, Parnian, Mohammadi, Arash, Tyrrell, Pascal N., Cheung, Patrick, Sigiuk, Ahmed, Plataniotis, Konstantinos N., Nguyen, Elsie T., Oikonomou, Anastasia
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/PMC7378058/
https://www.ncbi.nlm.nih.gov/pubmed/32703973
http://dx.doi.org/10.1038/s41598-020-69106-8

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7378058/
https://www.ncbi.nlm.nih.gov/pubmed/32703973
http://dx.doi.org/10.1038/s41598-020-69106-8

Ejemplares similares