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. 2025 Apr;32(4):2663-2664.
doi: 10.1245/s10434-024-16772-x. Epub 2025 Jan 3.

ASO Author Reflections: Leveraging Machine Learning for Early Recurrence Prediction in Gastric Cancer: Insights from a Multicenter Real-World Study

Xing-Qi Zhang  1   2   3 , Ze-Ning Huang  1   2   3 , Yan-Bing Zhou  4 , Jian-Xian Lin  1   2   3 , Chang-Ming Huang  5   6   7
Affiliations

ASO Author Reflections: Leveraging Machine Learning for Early Recurrence Prediction in Gastric Cancer: Insights from a Multicenter Real-World Study

Xing-Qi Zhang et al. Ann Surg Oncol. 2025 Apr.
No abstract available

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Conflict of interest statement

Disclosures: The authors declare that they have no conflict of interest.

References

    1. Mengxuan C, Can H, Siwei P, et al. Development and validation of nomogram for predicting early recurrence after radical gastrectomy of gastric cancer. World J Surg Oncol. 2024;22(1). https://doi.org/10.1186/s12957-023-03294-1
    1. Xing-Qi Z, Ze-Ning H, Ju W, et al. Machine learning prediction of early recurrence in gastric cancer: a nationwide real-world study. Ann Surg Oncol. 2024. https://doi.org/10.1245/s10434-024-16701-y . - DOI
    1. Liu G, Zhao L, Lv M. Defining a Nomogram for Predicting Early Recurrence in Gastric Cancer Patients After Neoadjuvant Chemotherapy and Radical Gastrectomy. J Gastrointest Surg Off J Soc Surg Aliment Tract. 2023;27(9):1766–77. https://doi.org/10.1007/s11605-023-05697-7 . - DOI
    1. Tetsuro T, Masanori T, Junki M, et al. Recurrence patterns after curative gastrectomy for pStage II/III gastric cancer: exploratory analysis of the randomized controlled JCOG1001 trial. Eur J Surg Oncol. 2022;49(4). https://doi.org/10.1016/j.ejso.2022.11.093
    1. Yoshiaki I, Masanori T, Junki M, et al. Gastrectomy with or without neoadjuvant S-1 plus cisplatin for type 4 or large type 3 gastric cancer (JCOG0501): an open-label, phase 3, randomized controlled trial. Gastric Cancer. 2020;24(2). https://doi.org/10.1007/s10120-020-01136-7

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