A Machine-Based Approach to Preoperatively Identify Patients with the Most and Least Benefit Associated with Resection for Intrahepatic Cholangiocarcinoma: An International Multi-institutional Analysis of 1146 Patients

Background Accurate risk stratification and patient selection is necessary to identify patients who will benefit the most from surgery or be better treated with other non-surgical treatment strategies. We sought to identify which patients in the preoperative setting would likely derive the most or l...

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Vydané v:	Annals of surgical oncology Ročník 27; číslo 4; s. 1110 - 1119
Hlavní autori:	Tsilimigras, Diamantis I., Mehta, Rittal, Moris, Dimitrios, Sahara, Kota, Bagante, Fabio, Paredes, Anghela Z., Moro, Amika, Guglielmi, Alfredo, Aldrighetti, Luca, Weiss, Matthew, Bauer, Todd W., Alexandrescu, Sorin, Poultsides, George A., Maithel, Shishir K., Marques, Hugo P., Martel, Guillaume, Pulitano, Carlo, Shen, Feng, Soubrane, Olivier, Koerkamp, Bas Groot, Endo, Itaru, Pawlik, Timothy M.
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Cham Springer International Publishing 01.04.2020 Springer Nature B.V
Predmet:	Aged Bile Duct Neoplasms - blood Bile Duct Neoplasms - mortality Bile Duct Neoplasms - surgery Bile Ducts, Intrahepatic Bilirubin Bilirubin - blood Biomarkers - blood Cholangiocarcinoma Cholangiocarcinoma - blood Cholangiocarcinoma - mortality Cholangiocarcinoma - surgery Databases, Factual Disease-Free Survival Female Hepatectomy Hepatobiliary Tumors Humans Learning algorithms Liver Neoplasms - surgery Lymph nodes Machine learning Male Medical prognosis Medicine Medicine & Public Health Metastases Middle Aged Oncology Patients Predictive Value of Tests Proportional Hazards Models Retrospective Studies Surgery Surgical Oncology Survival Time Factors Treatment Outcome Tumors
ISSN:	1068-9265, 1534-4681, 1534-4681
On-line prístup:	Získať plný text
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