… As the adoption of electronic health records (EHRs) has made it easier to access and aggregate
clinical data, there has been growing interest in conducting research with data collected …

… studies using real-world data, including those obtained from the electronic health record (EHR). …
and quality of the studies and the EHR data they purported to analyze. These retractions …

… To conduct a systematic review of deep learning models for electronic health record (EHR)
data, and illustrate various deep learning architectures for analyzing different data sources …

… “big data AND Electronic Health Records” and “data mining AND Electronic Health Records”…
mining of electronic health record data. J Am Med Inform Assoc 2013;20(e1):e118-24. 87. …

… electronic health records (EHRs) and the growing wealth of digitized information sources about
patients is ushering in an era of ‘Big Data… limitations: important data elements are missing …

… Conclusions With the burgeoning increase in the amount of electronic healthcare data,
the potential for knowledge discovery is significant if data are managed in innovative and …

… support tools that use electronic health record data and proposes potential solutions to …
data, and algorithms that do not provide information that is clinically meaningful. Existing health …

… validity, patient obligation to participate in the learning health system, and … health data.
Attention to these ethical issues is paramount to our realizing the benefits of electronic health data…

… Strengths and limitations of this study In this study, we show the importance of healthcare
processes in analysis of electronic health record (EHR) data using a large patient population …

… methods for electronic health record (EHR) data quality … of EHR data, which we define as
all data potentially recorded within the patient record, including billing and administrative data, …