Using Machine Learning Algorithms to Predict Hospital Acquired Thrombocytopenia after Operation in the Intensive Care Unit: A Retrospective Cohort Study

Using Machine Learning Algorithms to Predict Hospital Acquired Thrombocytopenia after Operation in the Intensive Care Unit: A Retrospective Cohort Study

Hospital acquired thrombocytopenia (HAT) is a common hematological complication after surgery. This research aimed to develop and compare the performance of seven machine learning (ML) algorithms for predicting patients that are at risk of HAT after surgery. We conducted a retrospective cohort study...

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Bibliographic Details
Main Authors: Yisong Cheng, Chaoyue Chen, Jie Yang, Hao Yang, Min Fu, Xi Zhong, Bo Wang, Min He, Zhi Hu, Zhongwei Zhang, Xiaodong Jin, Yan Kang, Qin Wu
Format: Article
Language:English
Published: MDPI AG 2021-09-01
Series:Diagnostics
Subjects:
hospital acquired thrombocytopenia
machine learning
predictive models
surgery
critical care
Online Access:https://www.mdpi.com/2075-4418/11/9/1614

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https://www.mdpi.com/2075-4418/11/9/1614

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