Author: Trentzsch, H.; Osterhoff, G.; Heller, R.; Nienaber, U.; Lazarovici, M.
                    Title: Herausforderungen der Digitalisierung in der Traumaversorgung  Cord-id: xnm5mlir  Document date: 2020_8_27
                    ID: xnm5mlir
                    
                    Snippet: The increasing digitalization of social life opens up new possibilities for modern health care. This article describes innovative application possibilities that could help to sustainably improve the treatment of severe injuries in the future with the help of methods such as big data, artificial intelligence, intelligence augmentation, and machine learning. For the successful application of these methods, suitable data sources must be available. The TraumaRegister DGU® (TR-DGU) currently represe
                    
                    
                    
                     
                    
                    
                    
                    
                        
                            
                                Document: The increasing digitalization of social life opens up new possibilities for modern health care. This article describes innovative application possibilities that could help to sustainably improve the treatment of severe injuries in the future with the help of methods such as big data, artificial intelligence, intelligence augmentation, and machine learning. For the successful application of these methods, suitable data sources must be available. The TraumaRegister DGU® (TR-DGU) currently represents the largest database in Germany in the field of care for severely injured patients that could potentially be used for digital innovations. In this context, it is a good example of the problem areas such as data transfer, interoperability, standardization of data sets, parameter definitions, and ensuring data protection, which still represent major challenges for the digitization of trauma care. In addition to the further development of new analysis methods, solutions must also continue to be sought to the question of how best to intelligently link the relevant data from the various data sources.
 
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