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http://scihub22266oqcxt.onion/ C5333224!5333224 !28269826     free     free     free Warning: file_get_contents(https://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?dbfrom=pubmed&id=28269826 &cmd=llinks): Failed to open stream: HTTP request failed! HTTP/1.1 429 Too Many Requests in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 215       AMIA+Annu+Symp+Proc 2016 ; 2016 (?): 319-325 Nephropedia Template TP {{tp|p=28269826 |t=2016. Hypothesis-Free Search for Connections between Birth Month and Disease Prevalence in Large, Geographically Varied Cohorts |pdf=|usr=}}{{28269826 }} gab.com Text Hypothesis-Free Search for Connections between Birth Month and Disease Prevalence in Large, Geographically Varied Cohorts JO: AMIA Annu Symp Proc http://www.kidney.de/pget.php?&tw=1&pmid=28269826 #FOAvip We have sought to replicate and extend the Season-wide Association Study (SeaWAS) of Boland, et al.(1) in identifying birth month-disease associations from electronic health records (EHRs). We used methodology similar to that implemented by Boland on three geographically distinct cohorts, for a total of 11.8 million individuals derived from multiple data sources. We were able to identify eleven out of sixteen literature-supported birth month associations as compared to seven of sixteen for SeaWAS. Of the nine novel cardiovascular birth month associations discovered by SeaWAS, we were able to replicate four. None of the novel non-cardiovascular associations discovered by SeaWAS emerged as significant relations in our study. We identified thirty birth month disease associations not previously reported; of those, only six associations were validated in more than one cohort. These results suggest that differences in cohort composition and location can cause consequential variation in results of hypothesis-free searches. Twit Text FOAVip Hypothesis-Free Search for Connections between Birth Month and Disease Prevalence in Large, Geographically Varied Cohorts ????AMIA Annu Symp Proc http://www.kidney.de/pget.php?&tw=1&pmid=28269826 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=28269826 #FOAvip English Wikipedia <ref>{{Cite pmid|28269826 }}</ref> Hypothesis-Free Search for Connections between Birth Month and Disease Prevalence in Large, Geographically Varied Cohorts #MMPMID28269826 Borsi JP AMIA Annu Symp Proc 2016[]; 2016 (?): 319-325 PMID28269826 show ga We have sought to replicate and extend the Season-wide Association Study (SeaWAS) of Boland, et al.(1) in identifying birth month-disease associations from electronic health records (EHRs). We used methodology similar to that implemented by Boland on three geographically distinct cohorts, for a total of 11.8 million individuals derived from multiple data sources. We were able to identify eleven out of sixteen literature-supported birth month associations as compared to seven of sixteen for SeaWAS. Of the nine novel cardiovascular birth month associations discovered by SeaWAS, we were able to replicate four. None of the novel non-cardiovascular associations discovered by SeaWAS emerged as significant relations in our study. We identified thirty birth month disease associations not previously reported; of those, only six associations were validated in more than one cohort. These results suggest that differences in cohort composition and location can cause consequential variation in results of hypothesis-free searches. |*Cohort Effect [MESH] |*Disease [MESH] |*Seasons [MESH] |Algorithms [MESH] |Data Mining [MESH] |Electronic Health Records [MESH] |Epidemiology [MESH] |Female [MESH] |Geography, Medical [MESH] |Humans [MESH] |Male [MESH] |Pregnancy [MESH] |Prevalence [MESH]Hypothesis-Free Search for Connections between Birth Month and Disease(epmc).pdf DeepDyve Pubget Overpricing