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http://scihub22266oqcxt.onion/ C4765679!4765679!26958281     free     free     free Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       AMIA+Annu+Symp+Proc 2015 ; 2015 (ä): 1821-30 Nephropedia Template TP {{tp|p=26958281|t=2015. Analyzing Self-Help Forums with Ontology-Based Text Mining: An Exploration in Kidney Space |pdf=|usr=}}{{26958281}} gab.com Text Analyzing Self-Help Forums with Ontology-Based Text Mining: An Exploration in Kidney Space JO: AMIA Annu Symp Proc http://www.kidney.de/pget.php?&tw=1&pmid=26958281 #FOAvip The Internet has emerged as a popular source for health-related information. More than eighty percent of American Internet users have searched for health topics online. Millions of patients use self-help online forums to exchange information and support. In parallel, the increasing prevalence of chronic diseases has become a financial burden for the healthcare system demanding new, cost-effective interventions. To provide such interventions, it is necessary to understand patients? preferences of treatment options and to gain insights into their experiences as patients. We introduce a text-processing algorithm based on semantic ontologies to allow for finer-grained analyses of online forums compared to standard methods. We have applied our method in an analysis of two major Chronic Kidney Disease (CKD) forums. Our results suggest that the analysis of forums may provide valuable insights on daily issues patients face, their choice of different treatment options and interactions between patients, their relatives and clinicians. Twit Text FOAVip Analyzing Self-Help Forums with Ontology-Based Text Mining: An Exploration in Kidney Space ????AMIA Annu Symp Proc http://www.kidney.de/pget.php?&tw=1&pmid=26958281 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=26958281 #FOAvip English Wikipedia <ref>{{Cite pmid|26958281}}</ref> Analyzing Self-Help Forums with Ontology-Based Text Mining: An Exploration in Kidney Space #MMPMID26958281 Burckhardt P; Padman R AMIA Annu Symp Proc 2015[]; 2015 (ä): 1821-30 PMID26958281show ga The Internet has emerged as a popular source for health-related information. More than eighty percent of American Internet users have searched for health topics online. Millions of patients use self-help online forums to exchange information and support. In parallel, the increasing prevalence of chronic diseases has become a financial burden for the healthcare system demanding new, cost-effective interventions. To provide such interventions, it is necessary to understand patients? preferences of treatment options and to gain insights into their experiences as patients. We introduce a text-processing algorithm based on semantic ontologies to allow for finer-grained analyses of online forums compared to standard methods. We have applied our method in an analysis of two major Chronic Kidney Disease (CKD) forums. Our results suggest that the analysis of forums may provide valuable insights on daily issues patients face, their choice of different treatment options and interactions between patients, their relatives and clinicians. äAnalyzing Self-Help Forums with Ontology-Based Text Mining: An Explora(epmc).pdf DeepDyve Pubget Overpricing