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10.1097/CIN.0000000000000907 http://scihub22266oqcxt.onion/10.1097/CIN.0000000000000907 35470304!9093222!35470304     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       Comput+Inform+Nurs 2022 ; 40 (5): 341-349 Nephropedia Template TP {{tp|p=35470304|t=2022. Predicting COVID-19 Cases Among Nurses Using Artificial Neural Network Approach |pdf=|usr=}}{{35470304}} gab.com Text Predicting COVID-19 Cases Among Nurses Using Artificial Neural Network Approach JO: Comput Inform Nurs http://www.kidney.de/pget.php?&tw=1&pmid=35470304 #FOAvip We designed a forecasting model to determine which frontline health workers are most likely to be infected by COVID-19 among 220 nurses. We used multivariate regression analysis and different classification algorithms to assess the effect of several covariates, including exposure to COVID-19 patients, access to personal protective equipment, proper use of personal protective equipment, adherence to hand hygiene principles, stressfulness, and training on the risk of a nurse being infected. Access to personal protective equipment and training were associated with a 0.19- and 1.66-point lower score in being infected by COVID-19. Exposure to COVID-19 cases and being stressed of COVID-19 infection were associated with a 0.016- and 9.3-point higher probability of being infected by COVID-19. Furthermore, an artificial neural network with 75.8% (95% confidence interval, 72.1-78.9) validation accuracy and 76.6% (95% confidence interval, 73.1-78.6) overall accuracy could classify normal and infected nurses. The neural network can help managers and policymakers determine which frontline health workers are most likely to be infected by COVID-19. Twit Text FOAVip Predicting COVID-19 Cases Among Nurses Using Artificial Neural Network Approach ????Comput Inform Nurs http://www.kidney.de/pget.php?&tw=1&pmid=35470304 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=35470304 #FOAvip English Wikipedia <ref>{{Cite pmid|35470304}}</ref> Predicting COVID-19 Cases Among Nurses Using Artificial Neural Network Approach #MMPMID35470304 Namdar P; Shafiekhani S; Teymori F; Abdollahzade S; Maleki A; Rafiei S Comput Inform Nurs 2022[May]; 40 (5): 341-349 PMID35470304show ga We designed a forecasting model to determine which frontline health workers are most likely to be infected by COVID-19 among 220 nurses. We used multivariate regression analysis and different classification algorithms to assess the effect of several covariates, including exposure to COVID-19 patients, access to personal protective equipment, proper use of personal protective equipment, adherence to hand hygiene principles, stressfulness, and training on the risk of a nurse being infected. Access to personal protective equipment and training were associated with a 0.19- and 1.66-point lower score in being infected by COVID-19. Exposure to COVID-19 cases and being stressed of COVID-19 infection were associated with a 0.016- and 9.3-point higher probability of being infected by COVID-19. Furthermore, an artificial neural network with 75.8% (95% confidence interval, 72.1-78.9) validation accuracy and 76.6% (95% confidence interval, 73.1-78.6) overall accuracy could classify normal and infected nurses. The neural network can help managers and policymakers determine which frontline health workers are most likely to be infected by COVID-19. |*COVID-19[MESH] |*Nurses[MESH] |Health Personnel[MESH] |Humans[MESH] |Neural Networks, Computer[MESH] |Personal Protective Equipment[MESH]Predicting COVID-19 Cases Among Nurses Using Artificial Neural Network(epmc).pdf DeepDyve Pubget Overpricing