Publications by authors named "Karni Marcus"
Estimation of postpartum depression risk from electronic health records using machine learning.
BMC Pregnancy Childbirth
September 2021
Background: Postpartum depression is a widespread disorder, adversely affecting the well-being of mothers and their newborns. We aim to utilize machine learning for predicting risk of postpartum depression (PPD) using primary care electronic health records (EHR) data, and to evaluate the potential value of EHR-based prediction in improving the accuracy of PPD screening and in early identification of women at risk.
Methods: We analyzed EHR data of 266,544 women from the UK who gave first live birth between 2000 and 2017.
Article Synopsis
- * Survey data provided a more sensitive detection of symptoms compared to electronic records, with common symptoms including fever, cough, and fatigue.
- * Key indicators of COVID-19 included loss of taste and smell occurring three weeks prior to testing, with children experiencing shorter illness duration and some symptoms persisting even after recovery.
Background: Reliably identifying patients at increased risk for coronavirus disease (COVID-19) complications could guide clinical decisions, public health policies, and preparedness efforts. Multiple studies have attempted to characterize at-risk patients, using various data sources and methodologies. Most of these studies, however, explored condition-specific patient cohorts (eg, hospitalized patients) or had limited access to patients' medical history, thus, investigating related questions and, potentially, obtaining biased results.
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