Early Identification of Maternal Cardiovascular Risk Through Sourcing and Preparing Electronic Health Record Data: Machine Learning Study.

Nawar Shara Kelley M Anderson Noor Falah Maryam F Ahmad Darya Tavazoei Justin M Hughes Bethany Talmadge Samantha Crovatt Ramon Dempers

Published in: JMIR medical informatics (2022)

Upon acquiring data, including their concatenation, anonymization, and normalization across multiple EHRs, the use of an ML-based tool can provide early identification of cardiovascular risk in pregnant patients.

Keyphrases

electronic health record
machine learning
end stage renal disease
clinical decision support
big data
chronic kidney disease
newly diagnosed
ejection fraction
adverse drug
prognostic factors
peritoneal dialysis
pregnant women
bioinformatics analysis