Prognostic prediction model for esophageal cancer based on probability membrane systems
Author:
Funder
National Natural Science Foundation of China
Publisher
Springer Science and Business Media LLC
Link
https://link.springer.com/content/pdf/10.1007/s41965-024-00151-2.pdf
Reference48 articles.
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2. Hirata, A., Hayano, K., Ohira, G., Imanishi, S., Hanaoka, T., Toyozumi, T., Murakami, K., Aoyagi, T., Shuto, K., & Matsubara, H. (2020). Volumetric histogram analysis of apparent diffusion coefficient as a biomarker to predict survival of esophageal cancer patients. Annals of Surgical Oncology, 27, 3083–3089.
3. Egmond, M. A., Schaaf, M., Klinkenbijl, J. H., Twisk, J. W., Engelbert, R. H., & Berge Henegouwen, M. I. (2020). The pre-and postoperative course of functional status in patients undergoing esophageal cancer surgery. European Journal of Surgical Oncology, 46(1), 173–179.
4. Pather, K., Mobley, E. M., Guerrier, C., Esma, R., Kendall, H., & Awad, Z. T. (2022). Long-term survival outcomes of esophageal cancer after minimally invasive ivor lewis esophagectomy. World Journal of Surgical Oncology, 20(1), 50.
5. Kang, M., Wang, Y., Yang, M., Wang, X., Zhu, L., & Zhang, M. (2023). Prognostic nomogram and risk factors for predicting survival in patients with pt2n0m0 esophageal squamous carcinoma. Scientific Reports, 13(1), 4931.
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