SwarmDeepSurv: swarm intelligence advances deep survival network for prognostic radiomics signatures in four solid cancers

Survival models exist to study relationships between biomarkers and treatment effects. Deep learning-powered survival models supersede the classical Cox proportional hazards (CoxPH) model, but substantial performance drops were observed on high-dimensional features because of irrelevant/redundant in...

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Detalles Bibliográficos
Autores principales: Al-Tashi, Qasem, Saad, Maliazurina B., Sheshadri, Ajay, Wu, Carol C., Chang, Joe Y., Al-Lazikani, Bissan, Gibbons, Christopher, Vokes, Natalie I., Zhang, Jianjun, Lee, J. Jack, Heymach, John V., Jaffray, David, Mirjalili, Seyedali, Wu, Jia
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2023
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10435962/
https://www.ncbi.nlm.nih.gov/pubmed/37602223
http://dx.doi.org/10.1016/j.patter.2023.100777

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10435962/
https://www.ncbi.nlm.nih.gov/pubmed/37602223
http://dx.doi.org/10.1016/j.patter.2023.100777

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