Published on in Vol 27 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/72638, first published .
Enhancing Pulmonary Disease Prediction Using Large Language Models With Feature Summarization and Hybrid Retrieval-Augmented Generation: Multicenter Methodological Study Based on Radiology Report

Enhancing Pulmonary Disease Prediction Using Large Language Models With Feature Summarization and Hybrid Retrieval-Augmented Generation: Multicenter Methodological Study Based on Radiology Report

Enhancing Pulmonary Disease Prediction Using Large Language Models With Feature Summarization and Hybrid Retrieval-Augmented Generation: Multicenter Methodological Study Based on Radiology Report

Ronghao Li   1 * ;   Shuai Mao   2 * ;   Congmin Zhu   1 , PhD ;   Yingliang Yang   1 ;   Chunting Tan   3 , PhD ;   Li Li   4 , PhD ;   Xiangdong Mu   4 , PhD ;   Honglei Liu   1 * , PhD ;   Yuqing Yang   2 * , PhD

1 School of Biomedical Engineering, Capital Medical University, Beijing, China

2 State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications, Beijing, China

3 Department of Respiratory Medicine, Beijing Friendship Hospital, Capital Medical University, Beijing, China

4 Beijing Respiratory and Critical Care Medicine Department, Tsinghua Changgung Hospital, School of Clinical Medicine, Tsinghua University, Beijing, China

*these authors contributed equally

Corresponding Author:

  • Honglei Liu, PhD
  • School of Biomedical Engineering
  • Capital Medical University
  • No. 10, Xitoutiao, You An Men, Fengtai District
  • Beijing 100069
  • China
  • Phone: 86 010-83911542
  • Email: liuhonglei@ccmu.edu.cn