Abstract

According to N. Goodman, the Carnapian notion of similarity is useless in science and without interest for philosophy. In our paper we suggest that, given the current role that the notion of similarity has in managing biomedical big data, this drastic position should be revised, and similarity should be provided a scientifically useful philosophical interpretation. With the advent of the new sequencing technologies, imaging technologies and with the improvements of health records, the number of genomics, post-genomics and clinical data has exponentially increased. The deluge of data has urged, among others, to devise a new way of stratifying patients. A solution has been found and it is based exactly on the notion of similarity. By discussing two examples focusing on similarity among breast cancer patients, in the paper we illustrate such a use, and analyze it from a philosophical standpoint by resorting to A. Tversky’s features matching approach. We believe that the latter can foster some better understanding of the meaning and current use of similarity in the context of biomedical big data, and that, therefore, be the focus of further reflections in the philosophy of science, in particular in the philosophy of biomedicine.