SpiroLLM: Finetuning Pretrained LLMs to Understand Spirogram Time Series with Clinical Validation in COPD Reporting

Introduction

SpiroLLM is the first multimodal large language model specifically designed to understand spirograms and aid in the diagnosis of Chronic Obstructive Pulmonary Disease (COPD).

Resource

• Paper: arxiv
• Code: Github
• Model: huggingface

If you find SpiroLLM useful for your work, please consider citing our work.

@misc{mei2025spirollmfinetuningpretrainedllms,
      title={SpiroLLM: Finetuning Pretrained LLMs to Understand Spirogram Time Series with Clinical Validation in COPD Reporting}, 
      author={Shuhao Mei and Yongchao Long and Shan Cao and Xiaobo Han and Shijia Geng and Jinbo Sun and Yuxi Zhou and Shenda Hong},
      year={2025},
      eprint={2507.16145},
      archivePrefix={arXiv},
      primaryClass={cs.AI},
      url={https://arxiv.org/abs/2507.16145}, 
}