Development and Validation of a Machine Learning–Based Prediction Model for Detection of Biliary Atresia

Development and Validation of a Machine Learning–Based Prediction Model for Detection of Biliary Atresia

Background and Aims: Biliary atresia is a rare and devastating bile duct disease that occurs during the neonatal period. Timely identification and prompt surgical intervention is critical for improving the outcome. The aim of the study was to develop a new machine learning–based prediction model for...

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Bibliographic Details
Main Authors: Ho Jung Choi, Yeong Eun Kim, Jung-Man Namgoong, Inki Kim, Jun Sung Park, Woo Im Baek, Byong Sop Lee, Hee Mang Yoon, Young Ah Cho, Jin Seong Lee, Jung Ok Shim, Seak Hee Oh, Jin Soo Moon, Jae Sung Ko, Dae Yeon Kim, Kyung Mo Kim
Format: Article
Language:English
Published: Elsevier 2023-01-01
Series:Gastro Hep Advances
Subjects:
Biliary Atresia
Neonatal Cholestasis
Prediction
Machine Learning
XGBoost
Online Access:http://www.sciencedirect.com/science/article/pii/S2772572323000766

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http://www.sciencedirect.com/science/article/pii/S2772572323000766

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