Predicting Rectal Cancer Response to Total Neoadjuvant Treatment Using an Artificial Intelligence Model Based on Magnetic Resonance Imaging and Clinical Data

Predicting Rectal Cancer Response to Total Neoadjuvant Treatment Using an Artificial Intelligence Model Based on Magnetic Resonance Imaging and Clinical Data

Purpose To develop a model for predicting response to total neoadjuvant treatment (TNT) for patients with locally advanced rectal cancer (LARC) based on baseline magnetic resonance imaging (MRI) and clinical data using artificial intelligence methods. Methods Baseline MRI and clinical data were cura...

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Bibliographic Details
Main Authors: Ganlu Ouyang MD, Zhebin Chen PhD, Meng Dou PhD, Xu Luo PhD, Han Wen PhD, Xiangbing Deng PhD, Wenjian Meng PhD, Yongyang Yu PhD, Bing Wu PhD, Dan Jiang PhD, Ziqiang Wang PhD, Yu Yao PhD, Xin Wang PhD
Format: Article
Language:English
Published: SAGE Publishing 2023-07-01
Series:Technology in Cancer Research & Treatment
Online Access:https://doi.org/10.1177/15330338231186467

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https://doi.org/10.1177/15330338231186467

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