ASO Author Reflections: Use of Machine Learning to Predict Early Recurrence After Resection of Intrahepatic Cholangiocarcinoma

被引：0
作者：
Laura Alaimo
Timothy M. Pawlik
机构：
[1] The Ohio State University Wexner Medical Center and James Comprehensive Cancer Center,Division of Surgical Oncology, Department of Surgery
[2] University of Verona,Department of Surgery
来源：
Annals of Surgical Oncology | 2023年 / 30卷
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页码：5416 / 5417
页数：1
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  • [2] Williams PJ(2017)Performance of prognostic scores and staging systems in predicting long-term survival outcomes after surgery for intrahepatic cholangiocarcinoma J Surg Oncol 116 1085-1095
  • [3] Claasen M(2022)Incorporating artificial intelligence in urology: supervised machine learning algorithms demonstrate comparative advantage over nomograms in predicting biochemical recurrence after prostatectomy Prostate 82 298-305
  • [4] Buettner S(2023)Development and validation of a machine learning model to predict early recurrence of intrahepatic cholangiocarcinoma Ann Surg Oncol 10 576901-undefined
  • [5] Galjart B(2020)A novel prognostic scoring system of intrahepatic cholangiocarcinoma with machine learning basing on real-world data Front Oncol. 13 5169-undefined
  • [6] van Vugt JLA(2021)Intrahepatic cholangiocarcinoma: a summative review of biomarkers and targeted therapies Cancers (Basel) undefined undefined-undefined
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