IKS index: A knowledge-model driven index to estimate the capability of medical diagnosis systems to produce results

The evaluation of a medical diagnosis system can depend on several external parameters, such as experts’ opinions/criteria or the gold standard used. In addition, there are other parameters that can be measured in a medical diagnosis system, and one of these parameters in particular is the sensitivity. Sensitivity allows knowing how sensible a system is to produce results in different environments. Hence, the aim of this paper is to provide researchers with an index able to estimate a parameter very similar to common sensitivity. This would permit to know an estimation of the results relying on the modeling of the knowledge base. It would be the mathematical justification of this index that would allow estimating the aforementioned parameter. Therefore, the index would in general allow an estimation of the sensitivity without the necessity of having external feedback from experts in the field, which is one of the main lacks within the classical sensitivity metric.