Editorial for “Fully Automated Identification of Lymph Node Metastases and Lymphovascular Invasion in Endometrial Cancer From Multi‐Parametric MRI by Deep Learning”
Author:
Affiliation:
1. Imaging Research Center Takatsuki General Hospital Takatsuki Japan
2. Department of Radiology Kobe University Graduate School of Medicine Kobe Japan
Publisher
Wiley
Link
https://onlinelibrary.wiley.com/doi/pdf/10.1002/jmri.29409
Reference9 articles.
1. The oncological and reproductive outcomes of fertility‐preserving treatments for stage 1 grade 1 endometrial carcinoma: A systematic review and meta‐analysis;Ogunbiyi MO;J Obstet Gynaecol,2024
2. Lymphadenectomy for the management of endometrial cancer;Frost JA;Cochrane Database Syst Rev,2017
3. Combined pelvic and para-aortic is superior to only pelvic lymphadenectomy in intermediate and high-risk endometrial cancer: a systematic review and meta-analysis
4. The Diagnostic Value of MRI for Preoperative Staging in Patients with Endometrial Cancer: A Meta-Analysis
5. Diagnostic Accuracy of Clinical Biomarkers for Preoperative Prediction of Lymph Node Metastasis in Endometrial Carcinoma: A Systematic Review and Meta-Analysis
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