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10.1093/jamia/ocv032 http://scihub22266oqcxt.onion/10.1093/jamia/ocv032 C4986665!4986665!25882031     free     free     free Deprecated: Implicit conversion from float 213.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 213.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 213.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       J+Am+Med+Inform+Assoc 2015 ; 22 (5): 938-47 Nephropedia Template TP {{tp|p=25882031|t=2015. Automated methods for the summarization of electronic health records |pdf=|usr=}}{{25882031}} gab.com Text Automated methods for the summarization of electronic health records JO: J Am Med Inform Assoc http://www.kidney.de/pget.php?&tw=1&pmid=25882031 #FOAvip 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 of EHR summarization implementation.Target audience The target audience for this review includes researchers, designers, and informaticians who are concerned about the problem of information overload in the clinical setting as well as both users and developers of clinical summarization systems.Scope Automated summarization has been a long-studied subject in the fields of natural language processing and human?computer interaction, but the translation of summarization and visualization methods to the complexity of the clinical workflow is slow moving. We assess work in aggregating and visualizing patient information with a particular focus on methods for detecting and removing redundancy, describing temporality, determining salience, accounting for missing data, and taking advantage of encoded clinical knowledge. We identify and discuss open challenges critical to the implementation and use of robust EHR summarization systems. Twit Text FOAVip Automated methods for the summarization of electronic health records ????J Am Med Inform Assoc http://www.kidney.de/pget.php?&tw=1&pmid=25882031 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=25882031 #FOAvip English Wikipedia <ref>{{Cite pmid|25882031}}</ref> Automated methods for the summarization of electronic health records #MMPMID25882031 Pivovarov R; Elhadad N J Am Med Inform Assoc 2015[Sep]; 22 (5): 938-47 PMID25882031show ga 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 of EHR summarization implementation.Target audience The target audience for this review includes researchers, designers, and informaticians who are concerned about the problem of information overload in the clinical setting as well as both users and developers of clinical summarization systems.Scope Automated summarization has been a long-studied subject in the fields of natural language processing and human?computer interaction, but the translation of summarization and visualization methods to the complexity of the clinical workflow is slow moving. We assess work in aggregating and visualizing patient information with a particular focus on methods for detecting and removing redundancy, describing temporality, determining salience, accounting for missing data, and taking advantage of encoded clinical knowledge. We identify and discuss open challenges critical to the implementation and use of robust EHR summarization systems. äAutomated methods for the summarization of electronic health records (epmc).pdf DeepDyve Pubget Overpricing