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This paper is in the following e-collection/theme issue:

Cancer Prognosis Models and Machine Learning (80) Clinical Information and Decision Making (2070) Machine Learning (2229) Innovations and Technology in Cancer Care (569) Clinical Cancer Research (134) Cancer Survivorship (361) Innovations in Cancer Diagnostic and Decision Support (121) Imaging Informatics (331) Obstetrics, Gynecology, and Reproductive Medicine (344)

Published on in Vol 11 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/69057, first published .
Machine Learning for Preoperative Assessment and Postoperative Prediction in Cervical Cancer: Multicenter Retrospective Model Integrating MRI and Clinicopathological Data

Machine Learning for Preoperative Assessment and Postoperative Prediction in Cervical Cancer: Multicenter Retrospective Model Integrating MRI and Clinicopathological Data

Machine Learning for Preoperative Assessment and Postoperative Prediction in Cervical Cancer: Multicenter Retrospective Model Integrating MRI and Clinicopathological Data

Authors of this article:

Shuqi Li1 Author Orcid Image ;   Chenyan Guo1 Author Orcid Image ;   Yufei Fang2 Author Orcid Image ;   Junjun Qiu1 Author Orcid Image ;   He Zhang1 Author Orcid Image ;   Lei Ling1 Author Orcid Image ;   Jie Xu3 Author Orcid Image ;   Xinwei Peng3 Author Orcid Image ;   Chuchu Jiang3 Author Orcid Image ;   Jue Wang1 Author Orcid Image ;   Keqin Hua1 Author Orcid Image
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Journals

  1. M D A, B V. SegResDeiT: a hybrid SegNet–ResNet-50–DeiT framework for automated cervical cancer segmentation and classification. BMC Medical Imaging 2025;25(1) View
  2. Zhu G, Chen C, Xiang Y, Wang Y, Zhong L, Lu Z. Machine learning-based prediction of long-term prognosis in cervical adenocarcinoma: a retrospective cohort study. BMC Cancer 2026;26(1) View