An Approach to Knowledge Base Construction Based on Expert Opinions

Abstract

Summary Objectives: To describe, validate and demonstrate an approach for knowledge base construction based on expert opinions. Methods: A knowledge base containing the frequency of occurrence of manifestations in epileptic seizures is constructed based on information provided by neurologists/epileptologists. The reliability of the responses is determined with the inter-rater intraclass correlation coefficient (ICC). If the ICC is not large enough the Spearman-Brown prophecy formula can be used to predict the number of additional experts. We propose a method to assess whether an additional expert provides information consistent with the already acquired data as well as a method to detect experts with deviating opinions. The power of the first method was determined. Results: Data were collected for five seizure types. The ICCs determined from the responses for the various seizure types after inclusion of the additional experts was in all cases almost equal to 0.9, the target value. Yet one expert with diverging opinions concerning the frequency of occurrence of manifestations for different seizure types could be identified. Excluding this participant improved the reliability of the data. The power of the methods was good (≥ 0.75). Conclusions: It is shown that human experts can provide reliable information about the frequency of occurrence of manifestations in epileptic seizures. In addition, the described approach correctly identified neurologists/epileptologists with both consistent and diverging opinions about the frequency of occurrence of manifestations in a number of seizure types.