A deep learning model for real-time mortality prediction in critically ill children

A deep learning model for real-time mortality prediction in critically ill children

Abstract Background The rapid development in big data analytics and the data-rich environment of intensive care units together provide unprecedented opportunities for medical breakthroughs in the field of critical care. We developed and validated a machine learning-based model, the Pediatric Risk of...

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Bibliographic Details
Main Authors: Soo Yeon Kim, Saehoon Kim, Joongbum Cho, Young Suh Kim, In Suk Sol, Youngchul Sung, Inhyeok Cho, Minseop Park, Haerin Jang, Yoon Hee Kim, Kyung Won Kim, Myung Hyun Sohn
Format: Article
Language:English
Published: BMC 2019-08-01
Series:Critical Care
Subjects:
Machine learning
Mortality
Intensive care units, pediatric
Prognosis
Risk assessment
Online Access:http://link.springer.com/article/10.1186/s13054-019-2561-z

Internet

http://link.springer.com/article/10.1186/s13054-019-2561-z

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