Deep Learning Model for Predicting the Pathological Complete Response to Neoadjuvant Chemoradiotherapy of Locally Advanced Rectal Cancer

Deep Learning Model for Predicting the Pathological Complete Response to Neoadjuvant Chemoradiotherapy of Locally Advanced Rectal Cancer

ObjectiveThis study aimed to develop an artificial intelligence model for predicting the pathological complete response (pCR) to neoadjuvant chemoradiotherapy (nCRT) of locally advanced rectal cancer (LARC) using digital pathological images.BackgroundnCRT followed by total mesorectal excision (TME)...

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Bibliographic Details
Main Authors: Xiaoying Lou, Niyun Zhou, Lili Feng, Zhenhui Li, Yuqi Fang, Xinjuan Fan, Yihong Ling, Hailing Liu, Xuan Zou, Jing Wang, Junzhou Huang, Jingping Yun, Jianhua Yao, Yan Huang
Format: Article
Language:English
Published: Frontiers Media S.A. 2022-06-01
Series:Frontiers in Oncology
Subjects:
rectal cancer
deep learning
neoadjuvant chemoradiotherapy
pathological complete response
artificial intelligence
Online Access:https://www.frontiersin.org/articles/10.3389/fonc.2022.807264/full

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https://www.frontiersin.org/articles/10.3389/fonc.2022.807264/full

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