Reply to Letter to the Editor: Nodal infiltration in endometrial cancer: a prediction model using best subset regression
Author:
Funder
Japan Society for the Promotion of Science
Publisher
Springer Science and Business Media LLC
Link
https://link.springer.com/content/pdf/10.1007/s00330-024-10861-x.pdf
Reference5 articles.
1. Matsumoto YK, Himoto Y, Nishio M et al (2023) Nodal infiltration in endometrial cancer: a prediction model using best subset regression. Eur Radiol. https://doi.org/10.1007/s00330-023-10310-1
2. Reijnen C, Gogou E, Visser NCM et al (2020) Preoperative risk stratification in endometrial cancer (ENDORISK) by a Bayesian network model: a development and validation study. PLoS Med 17:e1003111
3. Berek JS, Matias-Guiu X, Creutzberg C et al (2023) FIGO staging of endometrial cancer: 2023. J Gynecol Oncol 34:e85
4. Yan BC, Li Y, Ma FH et al (2021) Radiologists with MRI-based radiomics aids to predict the pelvic lymph node metastasis in endometrial cancer: a multicenter study. Eur Radiol 31:411–422
5. Otani S, Himoto Y, Nishio M et al (2022) Radiomic machine learning for pretreatment assessment of prognostic risk factors for endometrial cancer and its effects on radiologists’ decisions of deep myometrial invasion. Magn Reson Imaging 85:161–167
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