PM2: A New Prompting Multi-modal Model Paradigm for Few-shot Medical Image Classification

arXiv:2404.08915v1 Announce Type: cross
Abstract: Few-shot learning has been successfully applied to medical image classification as only very few medical examples are available for training. Due to the challenging problem of limited number of annotated medical images, image representations should not be solely derived from a single image modality which is insufficient for characterizing concept classes. In this paper, we propose a new prompting multi-modal model paradigm on medical image classification based on multi-modal foundation models, called PM2. Besides image …

abstract arxiv classification cs.cv cs.lg examples few-shot few-shot learning image images medical modal multi-modal paradigm prompting training type