Cargando…
Deep-learning-based survival prediction of patients with cutaneous malignant melanoma
BACKGROUND: This study obtained data on patients with cutaneous malignant melanoma (CMM) from the Surveillance, Epidemiology, and End Results (SEER) database, and used a deep learning and neural network (DeepSurv) model to predict the survival rate of patients with CMM and evaluate its effectiveness...
Autores principales: | Yu, Hai, Yang, Wei, Wu, Shi, Xi, Shaohui, Xia, Xichun, Zhao, Qi, Ming, Wai-kit, Wu, Lifang, Hu, Yunfeng, Deng, Liehua, Lyu, Jun |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10084770/ https://www.ncbi.nlm.nih.gov/pubmed/37051218 http://dx.doi.org/10.3389/fmed.2023.1165865 |
Ejemplares similares
-
A prognostic nomogram for the cancer-specific survival of white patients with invasive melanoma at BANS sites based on the Surveillance, Epidemiology, and End Results database
por: Huang, Jia-nan, et al.
Publicado: (2023) -
Deep-learning-based survival prediction of patients with lower limb melanoma
por: Zhang, Jinrong, et al.
Publicado: (2023) -
A nomogram for predicting survival in patients with skin non-keratinizing large cell squamous cell carcinoma: A study based on the Surveillance, Epidemiology, and End Results database
por: Zhang, Jinrong, et al.
Publicado: (2023) -
Crafting a prognostic nomogram for the overall survival rate of cutaneous verrucous carcinoma using the surveillance, epidemiology, and end results database
por: Chong, Siomui, et al.
Publicado: (2023) -
Prognosis of the Keratinizing Squamous Cell Carcinoma of the Tongue Based on Surveillance, Epidemiology, and End Results Database
por: Yu, Hai, et al.
Publicado: (2023)