Optimisation and evaluation of the random forest model in the efficacy prediction of chemoradiotherapy for advanced cervical cancer based on radiomics signature from high-resolution T2 weighted images

PURPOSE: Our objective was to establish a random forest model and to evaluate its predictive capability of the treatment effect of neoadjuvant chemotherapy–radiation therapy. METHODS: This retrospective study included 82 patients with locally advanced cervical cancer who underwent scanning from Marc...

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Detalles Bibliográficos
Autores principales: Liu, Defeng, Zhang, Xiaohang, Zheng, Tao, Shi, Qinglei, Cui, Yujie, Wang, Yongji, Liu, Lanxiang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Berlin Heidelberg 2021
Materias:
Gynecologic Oncology
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7960581/
https://www.ncbi.nlm.nih.gov/pubmed/33394142
http://dx.doi.org/10.1007/s00404-020-05908-5

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7960581/
https://www.ncbi.nlm.nih.gov/pubmed/33394142
http://dx.doi.org/10.1007/s00404-020-05908-5

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