Estimation of TP53 mutations for endometrial cancer based on diffusion-weighted imaging deep learning and radiomics features

Estimation of TP53 mutations for endometrial cancer based on diffusion-weighted imaging deep learning and radiomics features

Abstract Objectives To construct a prediction model based on deep learning (DL) and radiomics features of diffusion weighted imaging (DWI), and clinical variables for evaluating TP53 mutations in endometrial cancer (EC). Methods DWI and clinical data from 155 EC patients were included in this study,...

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Bibliographic Details
Main Authors: Lei Shen, Bo Dai, Shewei Dou, Fengshan Yan, Tianyun Yang, Yaping Wu
Format: Article
Language:English
Published: BMC 2025-01-01
Series:BMC Cancer
Subjects:
Endometrial cancer
TP53 mutation
Diffusion-weighted imaging
Radiomics
Deep learning
Online Access:https://doi.org/10.1186/s12885-025-13424-5
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https://doi.org/10.1186/s12885-025-13424-5

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