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--- |
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license: cc-by-nc-sa-4.0 |
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language: |
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- en |
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base_model: |
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- meta-llama/Llama-3.1-8B-Instruct |
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--- |
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# SpiroLLM: Finetuning Pretrained LLMs to Understand Spirogram Time Series with Clinical Validation in COPD Reporting |
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## Introduction |
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SpiroLLM is the **first** multimodal large language model specifically designed to understand spirograms and aid in the diagnosis of Chronic Obstructive Pulmonary Disease (COPD). |
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## Resource |
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- **Paper**: [arxiv](https://arxiv.org/abs/2507.16145) |
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- **Code**: [Github](https://github.com/yudaleng/SpiroLLM) |
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- **Model**: [huggingface](https://huggingface.co/yudaleng/SpiroLLM) |
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If you find SpiroLLM useful for your work, please consider citing our work. |
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``` |
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@misc{mei2025spirollmfinetuningpretrainedllms, |
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title={SpiroLLM: Finetuning Pretrained LLMs to Understand Spirogram Time Series with Clinical Validation in COPD Reporting}, |
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author={Shuhao Mei and Yongchao Long and Shan Cao and Xiaobo Han and Shijia Geng and Jinbo Sun and Yuxi Zhou and Shenda Hong}, |
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year={2025}, |
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eprint={2507.16145}, |
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archivePrefix={arXiv}, |
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primaryClass={cs.AI}, |
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url={https://arxiv.org/abs/2507.16145}, |
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} |
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``` |
