Transformer-Based Classification Outcome Prediction for Multimodal Stroke Treatment

arXiv:2404.12634v1 Announce Type: cross
Abstract: This study proposes a multi-modal fusion framework Multitrans based on the Transformer architecture and self-attention mechanism. This architecture combines the study of non-contrast computed tomography (NCCT) images and discharge diagnosis reports of patients undergoing stroke treatment, using a variety of methods based on Transformer architecture approach to predicting functional outcomes of stroke treatment. The results show that the performance of single-modal text classification is significantly better than single-modal image classification, but the effect of multi-modal …

abstract architecture arxiv attention classification contrast cs.ai cs.cv cs.lg diagnosis framework fusion images modal multi-modal multimodal patients prediction reports self-attention stroke study transformer transformer architecture treatment type