M. S. Ong, F. Magrabi and E. Coiera. (2012). Automated identification of extreme-risk events in clinical incident reports. J Am Med Inform Assoc (Vol. 19, pp. e110-8).
Abstract: OBJECTIVES: To explore the feasibility of using statistical text classification to automatically detect extreme-risk events in clinical incident reports. METHODS: Statistical text classifiers based on Naive Bayes and Support Vector Machine (SVM) algorithms were trained and tested on clinical incident reports to automatically detect extreme-risk events, defined by incidents that satisfy the criteria of