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The Application of Artificial Intelligence to Investigate Long-Term Outcomes and Assess Optimal Margin Width in Hepatectomy for Intrahepatic Cholangiocarcinoma

Laura Alaimo, Zorays Moazzam, Yutaka Endo, Henrique A. Lima, Swatika Butey, Andrea Ruzzenente, Alfredo Guglielmi, Luca Aldrighetti, Matthew J. Weiss, Todd W. Bauer, Sorin Alexandrescu, George A. Poultsides, Shishir K. Maithel, Hugo P. Marques, Guillaume Martel, Carlo Pulitanò, Feng Shen, François Cauchy, Bas Groot Koerkamp, Itaru Endo, Minoru Kitago, Alex Kim, Aslam Ejaz, Joal D. Beane, Jordan M. Cloyd, Timothy M. Pawlik

2023Annals of Surgical Oncology12 citationsDOIOpen Access PDF

Topics & Concepts

Surgical oncologyMedicineHepatectomyIntrahepatic CholangiocarcinomaMargin (machine learning)Term (time)OncologyGeneral surgeryInternal medicineResectionSurgeryComputer scienceMachine learningQuantum mechanicsPhysicsCholangiocarcinoma and Gallbladder Cancer StudiesGallbladder and Bile Duct DisordersHepatocellular Carcinoma Treatment and Prognosis
The Application of Artificial Intelligence to Investigate Long-Term Outcomes and Assess Optimal Margin Width in Hepatectomy for Intrahepatic Cholangiocarcinoma | Litcius