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10.1007/978-3-319-08416-9_13 http://scihub22266oqcxt.onion/10.1007/978-3-319-08416-9_13 C4795902!4795902!26998530     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 Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       Smart+Health 2014 ; 8549 (ä): 130-41 Nephropedia Template TP {{tp|p=26998530|t=2014. Trend and Network Analysis of Common Eligibility Features for Cancer Trials in ClinicalTrials gov |pdf=|usr=}}{{26998530}} gab.com Text Trend and Network Analysis of Common Eligibility Features for Cancer Trials in ClinicalTrials gov JO: Smart Health http://www.kidney.de/pget.php?&tw=1&pmid=26998530 #FOAvip ClinicalTrials.gov has been archiving clinical trials since 1999, with > 165,000 trials at present. It is a valuable but relatively untapped resource for understanding trial design patterns and acquiring reusable trial design knowledge. We extracted common eligibility features using an unsupervised tag-mining method and mined their temporal usage patterns in clinical trials on various cancers. We then employed trend and network analysis to investigate two questions: (1) what eligibility features are frequently used to select patients for clinical trials within one cancer or across multiple cancers; and (2) what are the trends in eligibility feature adoption or discontinuation across cancer research domains? Our results showed that each cancer domain reuses a small set of eligibility features frequently for selecting cancer trial patients and some features are shared across different cancers, with value range adjustments for numerical measures. We discuss the implications for facilitating community-based clinical research knowledge sharing and reuse. Twit Text FOAVip Trend and Network Analysis of Common Eligibility Features for Cancer Trials in ClinicalTrials gov ????Smart Health http://www.kidney.de/pget.php?&tw=1&pmid=26998530 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=26998530 #FOAvip English Wikipedia <ref>{{Cite pmid|26998530}}</ref> Trend and Network Analysis of Common Eligibility Features for Cancer Trials in ClinicalTrials gov #MMPMID26998530 Weng C; Yaman A; Lin K; He Z Smart Health 2014[Jul]; 8549 (ä): 130-41 PMID26998530show ga ClinicalTrials.gov has been archiving clinical trials since 1999, with > 165,000 trials at present. It is a valuable but relatively untapped resource for understanding trial design patterns and acquiring reusable trial design knowledge. We extracted common eligibility features using an unsupervised tag-mining method and mined their temporal usage patterns in clinical trials on various cancers. We then employed trend and network analysis to investigate two questions: (1) what eligibility features are frequently used to select patients for clinical trials within one cancer or across multiple cancers; and (2) what are the trends in eligibility feature adoption or discontinuation across cancer research domains? Our results showed that each cancer domain reuses a small set of eligibility features frequently for selecting cancer trial patients and some features are shared across different cancers, with value range adjustments for numerical measures. We discuss the implications for facilitating community-based clinical research knowledge sharing and reuse. äTrend and Network Analysis of Common Eligibility Features for Cancer T(epmc).pdf DeepDyve Pubget Overpricing