mlsanityData to 14 Oct 2026

Transformer-Based Classification Outcome Prediction for Multimodal Stroke Treatment

arXiv 2404.12634 ↗First posted 19 Apr 2024cs.CV cs.AI cs.LGcited by 11

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Abstract (arXiv)

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 combination is better than any single modality. Although the Transformer model only performs worse on imaging data, when combined with clinical meta-diagnostic information, both can learn better complementary information and make good contributions to accurately predicting stroke treatment effects..

Key facts. Cited by 11 papers in the map (data through 14 Oct 2026). Builds on 11 of its 28 references that are in the map. First posted on arXiv 19 Apr 2024.

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11 of 28 references.

References · 11

  1. 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,399
  2. 2020An Image is Worth 16x16 Words: Transformers for Image Recognition at Scalecited by 30,186
  3. 2019RoBERTa: A Robustly Optimized BERT Pretraining Approachcited by 13,372
  4. 2021Swin Transformer: Hierarchical Vision Transformer using Shifted Windowscited by 12,139
  5. 2019ALBERT: A Lite BERT for Self-supervised Learning of Language Representationscited by 2,790
  6. 2021TransUNet: Transformers Make Strong Encoders for Medical Image Segmentationcited by 1,558
  7. 2022DeiT III: Revenge of the ViTcited by 419
  8. 2023Generative Text-Guided 3D Vision-Language Pretraining for Unified Medical Image Segmentationcited by 47
  9. 2024A Multimodal Fusion Network For Student Emotion Recognition Based on Transformer and Tensor Productcited by 22
  10. 2024Utilizing the LightGBM Algorithm for Operator User Credit Assessment Researchcited by 12
  11. 2023TranSOP: Transformer-based Multimodal Classification for Stroke Treatment Outcome Predictioncited by 3

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2024: 9; 2025: 1; 2026: 1.

11 papers.

  1. 2024YOLO-PPA based Efficient Traffic Sign Detection for Cruise Control in Autonomous Drivingcited by 16
  2. 2024AR Overlay: Training Image Pose Estimation on Curved Surface in a Synthetic Waycited by 15
  3. 2024A Neural Matrix Decomposition Recommender System Model based on the Multimodal Large Language Modelcited by 12
  4. 2024Research on Key Technologies for Cross-Cloud Federated Training of Large Language Modelscited by 4
  5. 2024Improved Unet model for brain tumor image segmentation based on ASPP-coordinate attention mechanismcited by 2
  6. 2024Enhancing Exchange Rate Forecasting with Explainable Deep Learning Modelscited by 2
  7. 2024Analysis of Financial Risk Behavior Prediction Using Deep Learning and Big Data Algorithmscited by 2
  8. 2024Detecting and Classifying Defective Products in Images Using YOLOcited by 2
  9. 2024Multi-modal clothing recommendation model based on large model and VAE enhancementcited by 1
  10. 2025Comparing Baseline and Day-1 Diffusion MRI Using Multimodal Deep Embeddings for Stroke Outcome Predictioncited by 0
  11. 2026Vision-Core Guided Contrastive Learning for Balanced Multi-modal Prognosis Prediction of Strokecited by 0