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Diabetic kidney disease (DKD) is one of the most frequent complications in diabetes associated with substantial morbidity and mortality. To accelerate DKD risk factor discovery, we present an ensemble feature selection approach to identify a robust set of discriminant factors using electronic medical records (EMRs).

We describe a stratified sampling design that combines electronic health records (EHRs) and United States Census (USC) data to construct the sampling frame and an algorithm to enrich the sample with individuals belonging to rarer strata.

We propose to use segment graph convolutional and recurrent neural networks (Seg-GCRNs), which use only word embedding and sentence syntactic dependencies, to classify relations from clinical notes without manual feature engineering. In this study, the relations between 2 medical concepts are classified by simultaneously learning representations of text segments in the context of sentence syntactic dependency: preceding, concept1, middle, concept2, and succeeding segments. Seg-GCRN was systematically evaluated on the i2b2/VA [...]

The aim of this study was to generate synthetic electronic health records (EHRs). The generated EHR data will be more realistic than those generated using the existing medical Generative Adversarial Network (medGAN) method.

The reduction and control over neonatal, infant, and maternal mortality is a collective mission of the World Health Organization under United Nations.

CancelRx allows prescribers to send electronic cancellation messages to pharmacies when medications are discontinued. Little is known about its functionality and impact on clinical workflows.

Inpatient providers are increasingly utilizing alternative communication modalities outside what has traditionally been used, including short messaging service text messaging and application-based chat tools. Text messaging that meets the recommendations of the Joint Commission ("secure text messaging") allows for the communication of sensitive patient information through an encrypted platform.

Thirty-day hospital readmissions are a quality metric for health care systems. Predictive models aim to identify patients likely to readmit to more effectively target preventive strategies. Many risk of readmission models have been developed on retrospective data, but prospective validation of readmission models is rare. To the best of our knowledge, none of these developed models have been evaluated or prospectively validated in a military hospital.

Integration of electronic health records (EHRs) data across sites and access to that data remain limited.