mlsanityData to 7 Oct 2026

UF-HOBI at "Discharge Me!": A Hybrid Solution for Discharge Summary Generation Through Prompt-based Tuning of GatorTronGPT Models

arXiv 2407.15359 ↗First posted 22 Jul 2024cs.CLcited by 3

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Abstract (arXiv)

Automatic generation of discharge summaries presents significant challenges due to the length of clinical documentation, the dispersed nature of patient information, and the diverse terminology used in healthcare. This paper presents a hybrid solution for generating discharge summary sections as part of our participation in the "Discharge Me!" Challenge at the BioNLP 2024 Shared Task. We developed a two-stage generation method using both extractive and abstractive techniques, in which we first apply name entity recognition (NER) to extract key clinical concepts, which are then used as input for a prompt-tuning-based GatorTronGPT model to generate coherent text for two important sections including "Brief Hospital Course" and "Discharge Instructions". Our system was ranked 5th in this challenge, achieving an overall score of 0.284. The results demonstrate the effectiveness of our hybrid solution in improving the quality of automated discharge section generation.

Key facts. Cited by 3 papers in the map (data through 7 Oct 2026). Builds on 16 of its 31 references that are in the map. First posted on arXiv 22 Jul 2024.

Builds on

16 of 31 references.

References · 16

  1. 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,204
  2. 2020Retrieval-Augmented Generation for Knowledge-Intensive NLP Taskscited by 9,160
  3. 2019BERTScore: Evaluating Text Generation with BERTcited by 5,462
  4. 2021The Power of Scale for Parameter-Efficient Prompt Tuningcited by 3,769
  5. 2021GPT Understands, Toocited by 715
  6. 2023AlignScore: Evaluating Factual Consistency with a Unified Alignment Functioncited by 284
  7. 2023Adapted Large Language Models Can Outperform Medical Experts in Clinical Text Summarizationcited by 244
  8. 2022GatorTron: A Large Clinical Language Model to Unlock Patient Information from Unstructured Electronic Health Recordscited by 238
  9. 2023A Study of Generative Large Language Model for Medical Research and Healthcarecited by 160
  10. 2021Retrieval Augmented Code Generation and Summarizationcited by 148
  11. 2023ACI-BENCH: a Novel Ambient Clinical Intelligence Dataset for Benchmarking Automatic Visit Note Generationcited by 116
  12. 2020Retrieval-Augmented Generation for Code Summarization via Hybrid GNNcited by 89
4 more
  1. 2020Generating SOAP Notes from Doctor-Patient Conversations Using Modular Summarization Techniquescited by 64
  2. 2022Automatic Text Summarization Methods: A Comprehensive Reviewcited by 17
  3. 2022Discharge Summary Hospital Course Summarisation of In Patient Electronic Health Record Text with Clinical Concept Guided Deep Pre-Trained Transformer Modelscited by 17
  4. 2024Automatic Summarization of Doctor-Patient Encounter Dialogues Using Large Language Model through Prompt Tuningcited by 5

Built on by

Cited by year (2026 to 7 Oct)

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

3 papers.

  1. 2024Overview of the First Shared Task on Clinical Text Generation: RRG24 and "Discharge Me!"cited by 19
  2. 2026CuraView: A Multi-Agent Framework for Medical Hallucination Detection with GraphRAG-Enhanced Knowledge Verificationcited by 1
  3. 2025LCDS: A Logic-Controlled Discharge Summary Generation System Supporting Source Attribution and Expert Reviewcited by 0