OBJECTIVE: To better understand the literature searching preferences of clinical providers we conducted an institution-wide survey assessing the most preferred knowledge searching techniques.
Journal of the American Medical Informatics Association : JAMIA
Apr 29, 2015
OBJECTIVE: Analysis of narrative (text) data from electronic health records (EHRs) can improve population-scale phenotyping for clinical and genetic research. Currently, selection of text features for phenotyping algorithms is slow and laborious, req...
Accurate electronic health records are important for clinical care and research as well as ensuring patient safety. It is crucial for misspelled words to be corrected in order to ensure that medical records are interpreted correctly. This paper descr...
Electronic medical records are emerging as a major source of data for clinical and translational research studies, although phenotypes of interest need to be accurately defined first. This article provides an overview of how to develop a phenotype al...
Journal of the American Medical Informatics Association : JAMIA
Apr 15, 2015
OBJECTIVES: This review examines work on automated summarization of electronic health record (EHR) data and in particular, individual patient record summarization. We organize the published research and highlight methodological challenges in the area...
BMC medical informatics and decision making
Apr 15, 2015
BACKGROUND: The widespread use of electronic health records (EHRs) has generated massive clinical data storage. Association rules mining is a feasible technique to convert this large amount of data into usable knowledge for clinical decision making, ...
Journal of the American Medical Informatics Association : JAMIA
Apr 9, 2015
OBJECTIVE: Extracting medical knowledge from electronic medical records requires automated approaches to combat scalability limitations and selection biases. However, existing machine learning approaches are often regarded by clinicians as black boxe...
OBJECTIVE: Data in electronic health records (EHRs) is being increasingly leveraged for secondary uses, ranging from biomedical association studies to comparative effectiveness. To perform studies at scale and transfer knowledge from one institution ...
IEEE journal of biomedical and health informatics
Mar 19, 2015
In this paper, a hierarchical learning algorithm is developed for classifying large-scale patient records, e.g., categorizing large-scale patient records into large numbers of known patient categories (i.e., thousands of known patient categories) for...
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