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Machine Learning-Based Analysis in the Management of Iatrogenic Bile Duct Injury During Cholecystectomy: a Nationwide Multicenter Study

Crossref DOI link: https://doi.org/10.1007/s11605-022-05398-7

Published Print: 2022-08

Update policy: https://doi.org/10.1016/elsevier_cm_policy

Authors

Lopez-Lopez, Victor https://orcid.org/0000-0003-1718-3352
Maupoey, Javier

López-Andujar, Rafael

Ramos, Emilio

Mils, Kristel

Martinez, Pedro Antonio

Valdivieso, Andres

Garcés-Albir, Marina

Sabater, Luis

Valladares, Luis Díez

Pérez, Sergio Annese

Flores, Benito

Brusadin, Roberto

Conesa, Asunción López

Cayuela, Valentin

Cortijo, Sagrario Martinez

Paterna, Sandra

Serrablo, Alejando

Sánchez-Cabús, Santiago

Gil, Antonio González

Masía, Jose Antonio González

Loinaz, Carmelo

Lucena, Jose Luis

Pastor, Patricia

Garcia-Zamora, Cristina

Calero, Alicia

Valiente, Juan

Minguillon, Antonio

Rotellar, Fernando

Ramia, Jose Manuel

Alcazar, Cándido

Aguilo, Javier

Cutillas, Jose

Kuemmerli, Christoph

Ruiperez-Valiente, Jose A.

Robles-Campos, Ricardo
Funding

Funding for this research was provided by:

Universidad de Murcia
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Text and Data Mining valid from 2022-08-01

Text and Data Mining valid from 2022-08-01

Version of Record valid from 2024-01-10
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This article is maintained by: Elsevier

Article Title: Machine Learning-Based Analysis in the Management of Iatrogenic Bile Duct Injury During Cholecystectomy: a Nationwide Multicenter Study

Journal Title: Journal of Gastrointestinal Surgery

CrossRef DOI link to publisher maintained version: https://doi.org/10.1007/s11605-022-05398-7

Content Type: article

Copyright: Copyright © 2022 The Author(s)