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10.3390/ijerph17238786 http://scihub22266oqcxt.onion/10.3390/ijerph17238786 33256160!7729623!33256160     free     free     free Deprecated: Implicit conversion from float 229.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 229.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 229.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 229.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 229.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       Int+J+Environ+Res+Public+Health 2020 ; 17 (23): ä Nephropedia Template TP {{tp|p=33256160|t=2020. Shifting the Paradigm: The Dress-COV Telegram Bot as a Tool for Participatory Medicine |pdf=|usr=}}{{33256160}} gab.com Text Shifting the Paradigm: The Dress-COV Telegram Bot as a Tool for Participatory Medicine JO: Int J Environ Res Public Health http://www.kidney.de/pget.php?&tw=1&pmid=33256160 #FOAvip Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic management is limited by great uncertainty, for both health systems and citizens. Facing this information gap requires a paradigm shift from traditional approaches to healthcare to the participatory model of improving health. This work describes the design and function of the Doing Risk sElf-assessment and Social health Support for COVID (Dress-COV) system. It aims to establish a lasting link between the user and the tool; thus, enabling modeling of the data to assess individual risk of infection, or developing complications, to improve the individual's self-empowerment. The system uses bot technology of the Telegram application. The risk assessment includes the collection of user responses and the modeling of data by machine learning models, with increasing appropriateness based on the number of users who join the system. The main results reflect: (a) the individual's compliance with the tool; (b) the security and versatility of the architecture; (c) support and promotion of self-management of behavior to accommodate surveillance system delays; (d) the potential to support territorial health providers, e.g., the daily efforts of general practitioners (during this pandemic, as well as in their routine practices). These results are unique to Dress-COV and distinguish our system from classical surveillance applications. Twit Text FOAVip Shifting the Paradigm: The Dress-COV Telegram Bot as a Tool for Participatory Medicine ????Int J Environ Res Public Health http://www.kidney.de/pget.php?&tw=1&pmid=33256160 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=33256160 #FOAvip English Wikipedia <ref>{{Cite pmid|33256160}}</ref> Shifting the Paradigm: The Dress-COV Telegram Bot as a Tool for Participatory Medicine #MMPMID33256160 Franchini M; Pieroni S; Martini N; Ripoli A; Chiappino D; Denoth F; Liebman MN; Molinaro S; Della Latta D Int J Environ Res Public Health 2020[Nov]; 17 (23): ä PMID33256160show ga Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic management is limited by great uncertainty, for both health systems and citizens. Facing this information gap requires a paradigm shift from traditional approaches to healthcare to the participatory model of improving health. This work describes the design and function of the Doing Risk sElf-assessment and Social health Support for COVID (Dress-COV) system. It aims to establish a lasting link between the user and the tool; thus, enabling modeling of the data to assess individual risk of infection, or developing complications, to improve the individual's self-empowerment. The system uses bot technology of the Telegram application. The risk assessment includes the collection of user responses and the modeling of data by machine learning models, with increasing appropriateness based on the number of users who join the system. The main results reflect: (a) the individual's compliance with the tool; (b) the security and versatility of the architecture; (c) support and promotion of self-management of behavior to accommodate surveillance system delays; (d) the potential to support territorial health providers, e.g., the daily efforts of general practitioners (during this pandemic, as well as in their routine practices). These results are unique to Dress-COV and distinguish our system from classical surveillance applications. |*COVID-19[MESH] |*Epidemiological Monitoring[MESH] |*Pandemics[MESH] |*Software[MESH] |Adult[MESH] |Databases, Factual[MESH] |Female[MESH] |Health Promotion[MESH] |Humans[MESH] |Italy[MESH] |Machine Learning[MESH] |Male[MESH] |Middle Aged[MESH] |Risk Assessment[MESH]Shifting the Paradigm: The Dress-COV Telegram Bot as a Tool for Partic(epmc).pdf DeepDyve Pubget Overpricing