Abstract
Patient safety has become an international priority with major research
programs being carried out. The aim of this research is to assess the concept
of patient safety. Two artificial neural network systems were designed by
using questionnaire for the classification of an idle and non-idle hospital.
After training and testing the systems results were obtained for classification
of data. The Two type of neural networks (Feed Forward Back propagation
and Competitive neural network architecture) were tested for sensitivity,
specificity and accuracy it was found that the Feed Forward Back propagation (FFBP) give more accurate results with an accuracy of 96.37%.
ABAYZEED, D (2021). Assessment Of Patient’s Safety. Afribary. Retrieved from https://tracking.afribary.com/works/assessment-of-patient-s-safety
ABAYZEED, DINA "Assessment Of Patient’s Safety" Afribary. Afribary, 19 May. 2021, https://tracking.afribary.com/works/assessment-of-patient-s-safety. Accessed 06 Nov. 2024.
ABAYZEED, DINA . "Assessment Of Patient’s Safety". Afribary, Afribary, 19 May. 2021. Web. 06 Nov. 2024. < https://tracking.afribary.com/works/assessment-of-patient-s-safety >.
ABAYZEED, DINA . "Assessment Of Patient’s Safety" Afribary (2021). Accessed November 06, 2024. https://tracking.afribary.com/works/assessment-of-patient-s-safety