Artificial Intelligence-Based Framework for Analyzing Health Care Staff Security Practice: Mapping Review and Simulation Study.
Prosper Kandabongee YengLivinus Obiora NwekeBian YangMuhammad Ali FauziEinar Arthur SnekkenesPublished in: JMIR medical informatics (2021)
The security practices of health care staff can be effectively analyzed using a two-class approach to detect malicious and nonmalicious security practices. Based on our comparative study, the algorithms that can effectively be used in related studies include random forest, decision tree, and SVM. Deviations of security practices from required health care staff's security behavior in the big data context can be analyzed with real access logs to define appropriate incentives for improving conscious care security practice.