D-Dimer Elevation Matters to Predict Covid-19 Severity: A Machine Learning Approach
Document Type
Article
Abstract
Although previous studies using limited data have documented an association of D-dimer levels with COVID-19 severity, the role of D-dimer in the progression of COVID-19 remains unclear and requires further investigation using data from larger cohorts. We used traditional statistical modeling and machine learning methods to examine critical factors influencing the D-dimer elevation and to characterize associated risk factors of D-dimer elevation over the course of inpatient admission. We identified 20 important features to predict D-dimer levels, some of which could be used to predict and prevent the D-dimer elevation. Laboratory monitoring of D-dimer level and its risk factors at early stage can mitigate severe or death cases in COVID-19.
Digital Object Identifier (DOI)
Publication Info
Published in Proceedings 2022 IEEE 10th International Conference on Healthcare Informatics Ichi 2022, 2022, pages 481-482.
APA Citation
Wu, Y., Wu, D., & Sudha Xirasagar. (2022). D-Dimer Elevation Matters to Predict COVID-19 Severity: A Machine Learning Approach. 2022 IEEE 10th International Conference on Healthcare Informatics (ICHI), 481–482. https://doi.org/10.1109/ICHI54592.2022.00078
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