International audienceA novel content-based information retrieval framework, designed to cover several medical applications, is presented in this paper. The presented framework allows the retrieval of possibly incomplete medical cases consisting of several images together with semantic information. It relies on a committee of decision trees, decision support tools well suited to process this type of information. In our proposed framework, images are characterized by their digital content. It was applied to two heterogeneous medical datasets for computer aided diagnosis: a diabetic retinopathy follow-up dataset (DRD) and a mammography screening dataset (DDSM). Measure of precision among the top five retrieved results of 0.788+-0.137 and 0.86...