This paper is in the following e-collection/theme issue:

Generative Language Models Including ChatGPT (708) Foundation Models and Their Applications in AI (51) Natural Language Processing (917) Medical imaging (110) Pulmonology, COPD (195)

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

Authors of this article:

Ronghao Li1 Author Orcid Image ;   Shuai Mao2 Author Orcid Image ;   Congmin Zhu1 Author Orcid Image ;   Yingliang Yang1 Author Orcid Image ;   Chunting Tan3 Author Orcid Image ;   Li Li4 Author Orcid Image ;   Xiangdong Mu4 Author Orcid Image ;   Honglei Liu1 Author Orcid Image ;   Yuqing Yang2 Author Orcid Image
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Journals

  1. Anghelescu A, Munteanu C, Anghelescu L, Onose G. ”A Midsummer Night’s Dream” quest for truth: From ChatGPT “hallucinations” to RAG reasoning and ACURAI precision — a scoping review on detection, minimizing, and (almost) complete error elimination and enhancing Large Language Models' re-liability. Balneo and PRM Research Journal 2025;16(Vol 16 No. 3):847 View