Methods for a similarity measure for clinical attributes based on survival data analysis.

In silico evaluation scenarios showed that the mean accuracy of biomarker detection in k = 10 most similar cases is higher (0.909-0.998) than for competing similarity measures, such as Heterogeneous Euclidian-Overlap Metric (0.657-0.831) and Discretized Value Difference Metric (0.535-0.671). The weight calculation method showed a more than six times (6.59-6.95) higher weight for biomarker attributes over non-biomarker attributes. These results suggest that the similarity measure described here is suitable for applications based on survival data.