Prediction of radiosensitivity and radiocurability using a novel supervised artificial neural network

Prediction of radiosensitivity and radiocurability using a novel supervised artificial neural network

Abstract Background Radiotherapy has been widely used to treat various cancers, but its efficacy depends on the individual involved. Traditional gene-based machine-learning models have been widely used to predict radiosensitivity. However, there is still a lack of emerging powerful models, artificia...

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Bibliographic Details
Main Authors: Zihang Zeng, Maoling Luo, Yangyi Li, Jiali Li, Zhengrong Huang, Yuxin Zeng, Yu Yuan, Mengqin Wang, Yuying Liu, Yan Gong, Conghua Xie
Format: Article
Language:English
Published: BMC 2022-12-01
Series:BMC Cancer
Subjects:
Computational Biology
High-Throughput Sequencing
Multi-Omics
Neural Network Models
Radiosensitivity
Online Access:https://doi.org/10.1186/s12885-022-10339-3

Internet

https://doi.org/10.1186/s12885-022-10339-3

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