The present study validates the expert system PNEUMON-IA. The aim of PNEUMON-IA is assessing the etiology of community-acquired pneumonias from clinical, radiological, and laboratory data obtained at the onset of the disease. Validation was performed using data from medical records of 76 patients with proven clinical diagnosis of pneumonia. The etiological diagnoses provided by PNEUMON-IA were compared to those established by five specialists unrelated to the development of the expert system. For each etiological possibility, both PNEUMON-IA and the experts provided a causal possibility, expressed as a linguistic label (i.e., "almost impossible"). Linguistic labels were then converted to numeric values. In the majority of cases, an etiological diagnosis was unavailable to be used as a gold standard. To overcome this limitation, distances between arrays of etiological possibilities given by specialists and by PNEUMON-IA were considered as an agreement measure between diagnoses. Cluster analysis based on those distances was used to classify PNEUMON-IA among experts. Results showed the same differences between specialists and PNEUMON-IA as among the specialists themselves. The method used to validate PNEUMON-IA could prove useful to assess the performance of expert systems in fields where no gold standard is available. © 1992.
|Journal||Computers and Biomedical Research|
|Publication status||Published - 1 Jan 1992|