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Deep learning-based prognosis prediction among preeclamptic pregnancies using electronic health record data

2022-04-05 obstetrics and gynecology Title + abstract only
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BackgroundPreeclampsia (PE) is one of the leading factors in maternal and perinatal mortality and morbidity worldwide with no known cure. Delivery timing is key to balancing maternal and fetal risk in pregnancies complicated by PE. Delivery timing of PE patients is traditionally determined by closely monitoring over a prolonged time. We developed and externally validated a deep learning models that can predict the time to delivery of PE patients, based on electronic health records (EHR) data by ...

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