Multimodal MRI radiomics-based stacking ensemble learning model with automatic segmentation for prognostic prediction of HIFU ablation of uterine fibroids: a multicenter study

Multimodal MRI radiomics-based stacking ensemble learning model with automatic segmentation for prognostic prediction of HIFU ablation of uterine fibroids: a multicenter study

ObjectivesTo evaluate the effectiveness of an MRI radiomics stacking ensemble learning model, which combines T2-weighted imaging (T2WI) and contrast-enhanced T1-weighted imaging (CE-T1WI) with deep learning-based automatic segmentation, for preoperative prediction of the prognosis of high-intensity...

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Bibliographic Details
Main Authors: Bing Wen, Chengwei Li, Qiuyi Cai, Dan Shen, Xinyi Bu, Fuqiang Zhou
Format: Article
Language:English
Published: Frontiers Media S.A. 2024-12-01
Series:Frontiers in Physiology
Subjects:
artificial intelligence
uterine fibroids
high intensity focused ultrasound
ensemble stacking model
magnetic resonance imaging
Online Access:https://www.frontiersin.org/articles/10.3389/fphys.2024.1507986/full
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