Machine Learning to Predict the Response to Lenvatinib Combined with Transarterial Chemoembolization for Unresectable Hepatocellular Carcinoma

SIMPLE SUMMARY: The objective response rate of lenvatinib combined with transarterial chemoembolization for unresectable hepatocellular carcinoma is unsatisfactory. We aimed to develop predictive models using demographic characteristics, pre-treatment serum biomarkers and tumor characteristics of un...

Descripción completa

Detalles Bibliográficos
Autores principales: Ma, Jun, Bo, Zhiyuan, Zhao, Zhengxiao, Yang, Jinhuan, Yang, Yan, Li, Haoqi, Yang, Yi, Wang, Jingxian, Su, Qing, Wang, Juejin, Chen, Kaiyu, Yu, Zhengping, Wang, Yi, Chen, Gang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9913670/
https://www.ncbi.nlm.nih.gov/pubmed/36765583
http://dx.doi.org/10.3390/cancers15030625

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9913670/
https://www.ncbi.nlm.nih.gov/pubmed/36765583
http://dx.doi.org/10.3390/cancers15030625

Ejemplares similares