Use of Machine Learning for Early Detection of Maternal Cardiovascular Conditions: Retrospective Study Using Electronic Health Record Data.
Nawar SharaRoxanne Mirabal-BeltranBethany TalmadgeNoor FalahMaryam F AhmadRamon DempersSamantha CrovattSteven EisenbergKelley M AndersonPublished in: JMIR cardio (2024)
This study provides additional evidence to support ML in obstetrical patients to enhance the early detection of cardiovascular conditions during pregnancy. ML can synthesize multiday patient presentations to enhance provider decision-making and potentially reduce maternal health disparities.
Keyphrases
- electronic health record
- machine learning
- end stage renal disease
- decision making
- healthcare
- ejection fraction
- public health
- clinical decision support
- chronic kidney disease
- birth weight
- pregnancy outcomes
- mental health
- big data
- peritoneal dialysis
- prognostic factors
- artificial intelligence
- adverse drug
- physical activity
- risk assessment
- climate change
- deep learning
- health insurance
- weight loss
- gestational age
- data analysis
- weight gain