MediFact at MEDIQA-M3G 2024: Medical Question Answering in Dermatology with Multimodal Learning

arXiv:2405.01583v1 Announce Type: cross
Abstract: The MEDIQA-M3G 2024 challenge necessitates novel solutions for Multilingual & Multimodal Medical Answer Generation in dermatology (wai Yim et al., 2024a). This paper addresses the limitations of traditional methods by proposing a weakly supervised learning approach for open-ended medical question-answering (QA). Our system leverages readily available MEDIQA-M3G images via a VGG16-CNN-SVM model, enabling multilingual (English, Chinese, Spanish) learning of informative skin condition representations. Using pre-trained QA models, we further bridge the gap between visual and …

abstract arxiv challenge cs.ai cs.cl cs.cv cs.lg dermatology limitations medical multilingual multimodal multimodal learning novel paper question question answering solutions supervised learning type