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10.1038/s41598-018-21779-y http://scihub22266oqcxt.onion/10.1038/s41598-018-21779-y C5852024!5852024!29540710     free     free     free Deprecated: Implicit conversion from float 219.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 219.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 219.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 219.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 219.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       Sci+Rep 2018 ; 8 (ä): ä Nephropedia Template TP {{tp|p=29540710|t=2018. An Epidemiological Human Disease Network Derived from Disease Co-occurrence in Taiwan |pdf=|usr=}}{{29540710}} gab.com Text An Epidemiological Human Disease Network Derived from Disease Co-occurrence in Taiwan JO: Sci Rep http://www.kidney.de/pget.php?&tw=1&pmid=29540710 #FOAvip In ?classic? biomedical research, diseases have usually been studied individually. The pioneering human disease network (HDN) studies jointly consider a large number of diseases, analyse their interconnections, and provide a more comprehensive description of diseases. However, most of the existing HDN studies are based on molecular information and can only partially describe disease interconnections. Building on the unique Taiwan National Health Insurance Research Database (NHIRD), in this study, we construct the epidemiological HDN (eHDN), where two diseases are concluded as interconnected if their observed probability of co-occurrence deviating that expected under independence. Advancing from the existing HDN, the eHDN can also accommodate non-molecular connections and have more important practical implications. Building on the network construction, we examine important network properties such as connectivity, module, hub, and others and describe their temporal patterns. This study is among the first to systematically construct the eHDN and can have important implications for human disease research and health care and management. Twit Text FOAVip An Epidemiological Human Disease Network Derived from Disease Co-occurrence in Taiwan ????Sci Rep http://www.kidney.de/pget.php?&tw=1&pmid=29540710 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=29540710 #FOAvip English Wikipedia <ref>{{Cite pmid|29540710}}</ref> An Epidemiological Human Disease Network Derived from Disease Co-occurrence in Taiwan #MMPMID29540710 Jiang Y; Ma S; Shia BC; Lee TS Sci Rep 2018[]; 8 (ä): ä PMID29540710show ga In ?classic? biomedical research, diseases have usually been studied individually. The pioneering human disease network (HDN) studies jointly consider a large number of diseases, analyse their interconnections, and provide a more comprehensive description of diseases. However, most of the existing HDN studies are based on molecular information and can only partially describe disease interconnections. Building on the unique Taiwan National Health Insurance Research Database (NHIRD), in this study, we construct the epidemiological HDN (eHDN), where two diseases are concluded as interconnected if their observed probability of co-occurrence deviating that expected under independence. Advancing from the existing HDN, the eHDN can also accommodate non-molecular connections and have more important practical implications. Building on the network construction, we examine important network properties such as connectivity, module, hub, and others and describe their temporal patterns. This study is among the first to systematically construct the eHDN and can have important implications for human disease research and health care and management. äAn Epidemiological Human Disease Network Derived from Disease Co-occur(epmc).pdf DeepDyve Pubget Overpricing