Random indexing has previously been successfully used for medical vocabulary expansion for Germanic languages. In this study, we used this approach to extract medical terms from a Japanese patient blog corpus. The corpus was segmented into semantic units by a semantic role labeller, and different pre-processing and parameter settings were then evaluated. The evaluation showed that similar settings are suitable for Japanese as for previously explored Germanic languages, and that distributional semantics is equally useful for semi-automatic expansion of Japanese medical vocabularies as for medical vocabularies in Germanic languages.