Predict Pregnancy Outcomes in the COVID-19 Pandemic Using Electronic Health Records and Machine Learning Approach
10th IEEE International Conference on Healthcare Informatics, ICHI 2022
; : 483, 2022.
Article
in English
| Scopus | ID: covidwho-2063255
ABSTRACT
COVID-19 negatively impacts maternal health. We use national electronic health records data and machine learning techniques to recognize risk factors that are predictive of negative maternal outcomes in the pandemic. The cohort has been built with 191,403 gestations. The findings of this study will help advance the clinical decision support system for preventing negative maternal outcomes and promoting maternal health. © 2022 IEEE.
COVID-19; electronic health records; machine learning; maternal health; Decision support systems; E-learning; eHealth; Health risks; Records management; Clinical decision support systems; Electronic health; Electronic health record; Health records; Machine learning approaches; Machine learning techniques; Machine-learning; Maternal healths; Risk factors
Full text:
Available
Collection:
Databases of international organizations
Database:
Scopus
Type of study:
Prognostic study
Language:
English
Journal:
10th IEEE International Conference on Healthcare Informatics, ICHI 2022
Year:
2022
Document Type:
Article
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