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10.1007/s10278-014-9698-8 http://scihub22266oqcxt.onion/10.1007/s10278-014-9698-8 C4391063!4391063!24865858     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 Warning: imagejpeg(C:\Inetpub\vhosts\kidney.de\httpdocs\phplern\24865858.jpg): Failed to open stream: No such file or directory in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 117       J+Digit+Imaging 2014 ; 27 (6): 702-13 Nephropedia Template TP {{tp|p=24865858|t=2014. Integrated Image Data and Medical Record Management for Rare Disease Registries A General Framework and its Instantiation to the German Calciphylaxis Registry |pdf=|usr=}}{{24865858}} gab.com Text Integrated Image Data and Medical Record Management for Rare Disease Registries A General Framework and its Instantiation to the German Calciphylaxis Registry JO: J Digit Imaging http://www.kidney.de/pget.php?&tw=1&pmid=24865858 #FOAvip Especially for investigator-initiated research at universities and academic institutions, Internet-based rare disease registries (RDR) are required that integrate electronic data capture (EDC) with automatic image analysis or manual image annotation. We propose a modular framework merging alpha-numerical and binary data capture. In concordance with the Office of Rare Diseases Research recommendations, a requirement analysis was performed based on several RDR databases currently hosted at Uniklinik RWTH Aachen, Germany. With respect to the study management tool that is already successfully operating at the Clinical Trial Center Aachen, the Google Web Toolkit was chosen with Hibernate and Gilead connecting a MySQL database management system. Image and signal data integration and processing is supported by Apache Commons FileUpload-Library and ImageJ-based Java code, respectively. As a proof of concept, the framework is instantiated to the German Calciphylaxis Registry. The framework is composed of five mandatory core modules: (1) Data Core, (2) EDC, (3) Access Control, (4) Audit Trail, and (5) Terminology as well as six optional modules: (6) Binary Large Object (BLOB), (7) BLOB Analysis, (8) Standard Operation Procedure, (9) Communication, (10) Pseudonymization, and (11) Biorepository. Modules 1?7 are implemented in the German Calciphylaxis Registry. The proposed RDR framework is easily instantiated and directly integrates image management and analysis. As open source software, it may assist improved data collection and analysis of rare diseases in near future. Twit Text FOAVip Integrated Image Data and Medical Record Management for Rare Disease Registries A General Framework and its Instantiation to the German Calciphylaxis Registry ????J Digit Imaging http://www.kidney.de/pget.php?&tw=1&pmid=24865858 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=24865858 #FOAvip English Wikipedia <ref>{{Cite pmid|24865858}}</ref> Integrated Image Data and Medical Record Management for Rare Disease Registries A General Framework and its Instantiation to the German Calciphylaxis Registry #MMPMID24865858 Deserno TM; Haak D; Brandenburg V; Deserno V; Classen C; Specht P J Digit Imaging 2014[Dec]; 27 (6): 702-13 PMID24865858show ga Especially for investigator-initiated research at universities and academic institutions, Internet-based rare disease registries (RDR) are required that integrate electronic data capture (EDC) with automatic image analysis or manual image annotation. We propose a modular framework merging alpha-numerical and binary data capture. In concordance with the Office of Rare Diseases Research recommendations, a requirement analysis was performed based on several RDR databases currently hosted at Uniklinik RWTH Aachen, Germany. With respect to the study management tool that is already successfully operating at the Clinical Trial Center Aachen, the Google Web Toolkit was chosen with Hibernate and Gilead connecting a MySQL database management system. Image and signal data integration and processing is supported by Apache Commons FileUpload-Library and ImageJ-based Java code, respectively. As a proof of concept, the framework is instantiated to the German Calciphylaxis Registry. The framework is composed of five mandatory core modules: (1) Data Core, (2) EDC, (3) Access Control, (4) Audit Trail, and (5) Terminology as well as six optional modules: (6) Binary Large Object (BLOB), (7) BLOB Analysis, (8) Standard Operation Procedure, (9) Communication, (10) Pseudonymization, and (11) Biorepository. Modules 1?7 are implemented in the German Calciphylaxis Registry. The proposed RDR framework is easily instantiated and directly integrates image management and analysis. As open source software, it may assist improved data collection and analysis of rare diseases in near future. äIntegrated Image Data and Medical Record Management for Rare Disease R(epmc).pdf DeepDyve Pubget Overpricing