Use my Search Websuite to scan PubMed, PMCentral, Journal Hosts and Journal Archives, FullText. Kick-your-searchterm to multiple Engines kick-your-query now !>

A dictionary by aggregated review articles of nephrology, medicine and the life sciences Your one-stop-run pathway from word to the immediate pdf of peer-reviewed on-topic knowledge.

http://scihub22266oqcxt.onion/ C4765586!4765586!26958189     free     free     free Deprecated: Implicit conversion from float 229.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       AMIA+Annu+Symp+Proc 2015 ; 2015 (ä): 553-9 Nephropedia Template TP {{tp|p=26958189|t=2015. Reviewing 741 patients records in two hours with FASTVISU |pdf=|usr=}}{{26958189}} gab.com Text Reviewing 741 patients records in two hours with FASTVISU JO: AMIA Annu Symp Proc http://www.kidney.de/pget.php?&tw=1&pmid=26958189 #FOAvip The secondary use of electronic health records opens up new perspectives. They provide researchers with structured data and unstructured data, including free text reports. Many applications been developed to leverage knowledge from free-text reports, but manual review of documents is still a complex process.We developed FASTVISU a web-based application to assist clinicians in reviewing documents. We used FASTVISU to review a set of 6340 documents from 741 patients suffering from the celiac disease.A first automated selection pruned the original set to 847 documents from 276 patients? records. The records were reviewed by two trained physicians to identify the presence of 15 auto-immune diseases. It took respectively two hours and two hours and a half to evaluate the entire corpus. Inter-annotator agreement was high (Cohen?s kappa at 0.89).FASTVISU is a user-friendly modular solution to validate entities extracted by NLP methods from free-text documents stored in clinical data warehouses. Twit Text FOAVip Reviewing 741 patients records in two hours with FASTVISU ????AMIA Annu Symp Proc http://www.kidney.de/pget.php?&tw=1&pmid=26958189 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=26958189 #FOAvip English Wikipedia <ref>{{Cite pmid|26958189}}</ref> Reviewing 741 patients records in two hours with FASTVISU #MMPMID26958189 Escudié JB; Jannot AS; Zapletal E; Cohen S; Malamut G; Burgun A; Rance B AMIA Annu Symp Proc 2015[]; 2015 (ä): 553-9 PMID26958189show ga The secondary use of electronic health records opens up new perspectives. They provide researchers with structured data and unstructured data, including free text reports. Many applications been developed to leverage knowledge from free-text reports, but manual review of documents is still a complex process.We developed FASTVISU a web-based application to assist clinicians in reviewing documents. We used FASTVISU to review a set of 6340 documents from 741 patients suffering from the celiac disease.A first automated selection pruned the original set to 847 documents from 276 patients? records. The records were reviewed by two trained physicians to identify the presence of 15 auto-immune diseases. It took respectively two hours and two hours and a half to evaluate the entire corpus. Inter-annotator agreement was high (Cohen?s kappa at 0.89).FASTVISU is a user-friendly modular solution to validate entities extracted by NLP methods from free-text documents stored in clinical data warehouses. äReviewing 741 patients records in two hours with FASTVISU (epmc).pdf DeepDyve Pubget Overpricing