mlsanityData to 14 Oct 2026

RadOnc-GPT: A Large Language Model for Radiation Oncology

arXiv 2309.10160 ↗First posted 18 Sep 2023physics.med-ph cs.AIcited by 18

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Abstract (arXiv)

This paper presents RadOnc-GPT, a large language model specialized for radiation oncology through advanced tuning methods. RadOnc-GPT was finetuned on a large dataset of radiation oncology patient records from the Mayo Clinic in Arizona. The model employs instruction tuning on three key tasks - generating radiotherapy treatment regimens, determining optimal radiation modalities, and providing diagnostic descriptions/ICD codes based on patient diagnostic details. Evaluations conducted by comparing RadOnc-GPT outputs to general large language model outputs showed higher ROUGE scores in these three tasks. The study demonstrated the potential of using large language models fine-tuned using domain-specific knowledge like RadOnc-GPT to achieve transformational capabilities in highly specialized healthcare fields such as radiation oncology. However, our model's clinical relevance requires confirmation, and it specializes in only the aforementioned three specific tasks and lacks broader applicability. Furthermore, its evaluation through ROUGE scores might not reflect the true semantic and clinical accuracy - challenges we intend to address in future research.

Key facts. Cited by 18 papers in the map (data through 14 Oct 2026). Builds on 24 of its 59 references that are in the map. First posted on arXiv 18 Sep 2023.

Builds on

24 of 59 references.

References · 24

  1. 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,399
  2. 2023GPT-4 Technical Reportcited by 18,396
  3. 2019RoBERTa: A Robustly Optimized BERT Pretraining Approachcited by 13,372
  4. 2022PaLM: Scaling Language Modeling with Pathwayscited by 5,326
  5. 2023A Comprehensive Survey on Pretrained Foundation Models: A History from BERT to ChatGPTcited by 368
  6. 2023DeID-GPT: Zero-shot Medical Text De-Identification by GPT-4cited by 130
  7. 2023Review of Large Vision Models and Visual Prompt Engineeringcited by 77
  8. 2023An Iterative Optimizing Framework for Radiology Report Summarization with ChatGPTcited by 57
  9. 2023When Brain-inspired AI Meets AGIcited by 54
  10. 2023Evaluating Large Language Models on a Highly-specialized Topic, Radiation Oncology Physicscited by 49
  11. 2023Radiology-GPT: A Large Language Model for Radiologycited by 44
  12. 2023SAMAug: Point Prompt Augmentation for Segment Anything Modelcited by 38
12 more
  1. 2023AD-AutoGPT: An Autonomous GPT for Alzheimer's Disease Infodemiologycited by 34
  2. 2023Context Matters: A Strategy to Pre-train Language Model for Science Educationcited by 32
  3. 2023Exploring the Trade-Offs: Unified Large Language Models vs Local Fine-Tuned Models for Highly-Specific Radiology NLI Taskcited by 32
  4. 2023Artificial General Intelligence for Medical Imaging Analysiscited by 32
  5. 2023Differentiate ChatGPT-generated and Human-written Medical Textscited by 26
  6. 2023Mask-guided BERT for Few Shot Text Classificationcited by 25
  7. 2023Segment Anything Model (SAM) for Radiation Oncologycited by 24
  8. 2023Exploring New Frontiers in Agricultural NLP: Investigating the Potential of Large Language Models for Food Applicationscited by 21
  9. 2023CohortGPT: An Enhanced GPT for Participant Recruitment in Clinical Studycited by 19
  10. 2023Exploring Multimodal Approaches for Alzheimer's Disease Detection Using Patient Speech Transcript and Audio Datacited by 13
  11. 2023Evaluating Large Language Models for Radiology Natural Language Processingcited by 12
  12. 2023Hierarchical Semantic Tree Concept Whitening for Interpretable Image Classificationcited by 5

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Citing papers per year: 2023: 5; 2024: 9; 2025: 4.

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  1. 2024Revolutionizing Finance with LLMs: An Overview of Applications and Insightscited by 90
  2. 2024Opportunities and Challenges of Large Language Models for Low-Resource Languages in Humanities Researchcited by 27
  3. 2023Multimodality of AI for Education: Towards Artificial General Intelligencecited by 21
  4. 2024Reasoning before Comparison: LLM-Enhanced Semantic Similarity Metrics for Domain Specialized Text Analysiscited by 21
  5. 2023Holistic Evaluation of GPT-4V for Biomedical Imagingcited by 19
  6. 2023On the Promises and Challenges of Multimodal Foundation Models for Geographical, Environmental, Agricultural, and Urban Planning Applicationscited by 15
  7. 2024Automated radiotherapy treatment planning guided by GPT-4Visioncited by 12
  8. 2024Transcending Language Boundaries: Harnessing LLMs for Low-Resource Language Translationcited by 12
  9. 2024GP-GPT: Large Language Model for Gene-Phenotype Mappingcited by 11
  10. 2023Benchmarking a foundation LLM on its ability to re-label structure names in accordance with the AAPM TG-263 reportcited by 5
  11. 2023Evaluating multiple large language models in pediatric ophthalmologycited by 4
  12. 2025Large Language Models for Bioinformaticscited by 3
6 more
  1. 2025Evaluating The Performance of Using Large Language Models to Automate Summarization of CT Simulation Orders in Radiation Oncologycited by 3
  2. 2024Retrospective Comparative Analysis of Prostate Cancer In-Basket Messages: Responses from Closed-Domain LLM vs. Clinical Teamscited by 2
  3. 2024EXACT-Net:EHR-guided lung tumor auto-segmentation for non-small cell lung cancer radiotherapycited by 1
  4. 2024A Survey for Large Language Models in Biomedicinecited by 1
  5. 2025A Language Vision Model Approach for Automated Tumor Contouring in Radiation Oncologycited by 1
  6. 2025An Automated Retrieval-Augmented Generation LLaMA-4 109B-based System for Evaluating Radiotherapy Treatment Planscited by 0