mlsanityData to 7 Oct 2026

Deep Learning for Medical Text Processing: BERT Model Fine-Tuning and Comparative Study

arXiv 2410.20792 ↗First posted 28 Oct 2024cs.CL cs.LGcited by 8

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Abstract (arXiv)

This paper proposes a medical literature summary generation method based on the BERT model to address the challenges brought by the current explosion of medical information. By fine-tuning and optimizing the BERT model, we develop an efficient summary generation system that can quickly extract key information from medical literature and generate coherent, accurate summaries. In the experiment, we compared various models, including Seq-Seq, Attention, Transformer, and BERT, and demonstrated that the improved BERT model offers significant advantages in the Rouge and Recall metrics. Furthermore, the results of this study highlight the potential of knowledge distillation techniques to further enhance model performance. The system has demonstrated strong versatility and efficiency in practical applications, offering a reliable tool for the rapid screening and analysis of medical literature.

Key facts. Cited by 8 papers in the map (data through 7 Oct 2026). Builds on 15 of its 24 references that are in the map. First posted on arXiv 28 Oct 2024.

Builds on

15 of 24 references.

References · 15

  1. 2024Transforming Multidimensional Time Series into Interpretable Event Sequences for Advanced Data Miningcited by 47
  2. 2024Research on Adverse Drug Reaction Prediction Model Combining Knowledge Graph Embedding and Deep Learningcited by 17
  3. 2024Adaptive Friction in Deep Learning: Enhancing Optimizers with Sigmoid and Tanh Functioncited by 16
  4. 2024Breast Cancer Image Classification Method Based on Deep Transfer Learningcited by 12
  5. 2024Dynamic Hypergraph-Enhanced Prediction of Sequential Medical Visitscited by 12
  6. 2024A Lightweight GAN-Based Image Fusion Algorithm for Visible and Infrared Imagescited by 11
  7. 2024Algorithm Research of ELMo Word Embedding and Deep Learning Multimodal Transformer in Image Descriptioncited by 10
  8. 2024Adversarial Neural Networks in Medical Imaging Advancements and Challenges in Semantic Segmentationcited by 10
  9. 2024Applying Conditional Generative Adversarial Networks for Imaging Diagnosiscited by 9
  10. 2024Enhancing Convolutional Neural Networks with Higher-Order Numerical Difference Methodscited by 8
  11. 2024Contrastive Learning for Knowledge-Based Question Generation in Large Language Modelscited by 8
  12. 2024Reducing Bias in Deep Learning Optimization: The RSGDM Approachcited by 7
3 more
  1. 2024Optimizing News Text Classification with Bi-LSTM and Attention Mechanism for Efficient Data Processingcited by 7
  2. 2024Comparative Analysis of Open-Source Language Models in Summarizing Medical Text Datacited by 4
  3. 2024Summarizing Radiology Reports Findings into Impressionscited by 1

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Cited by year

Citing papers per year: 2024: 8.

8 papers.

  1. 2024Emotion-Aware Interaction Design in Intelligent User Interface Using Multi-Modal Deep Learningcited by 13
  2. 2024Adaptive Optimization for Enhanced Efficiency in Large-Scale Language Model Trainingcited by 13
  3. 2024Self-Supervised Learning in Deep Networks: A Pathway to Robust Few-Shot Classificationcited by 11
  4. 2024An Automated Data Mining Framework Using Autoencoders for Feature Extraction and Dimensionality Reductioncited by 9
  5. 2024A Combined Encoder and Transformer Approach for Coherent and High-Quality Text Generationcited by 7
  6. 2024AI-Driven Health Monitoring of Distributed Computing Architecture: Insights from XGBoost and SHAPcited by 7
  7. 2024Optimizing Multi-Task Learning for Enhanced Performance in Large Language Modelscited by 5
  8. 2024Dynamic User Interface Generation for Enhanced Human-Computer Interaction Using Variational Autoencoderscited by 2