Lung-R1: A Knowledge Graph-Guided LLM for Pulmonary Diagnostic Reasoning
Diagnosing pulmonary diseases requires integrating heterogeneous evidence amid phenotypic variability and cross-disease overlap. Although large language models (LLMs) have shown progress on pulmonary knowledge question answering (QA) and information-processing tasks, reliable pulmonary diagnosis requires patient-specific, relation-aware reasoning over electronic medical record (EMR) evidence rather than isolated knowledge recall. We define this gap between pulmonary knowledge and case-level diagnostic reasoning as the Pulmonary Knowledge-to-Diagnosis Gap. To address it, we introduce LungKG, the first structured pulmonary knowledge graph for diagnostic knowledge organization and record-gro...
| Authors | Haoyang Zeng, Yuanxi Fu, Rongzhen Li et al. |
|---|---|
| Primary category | cs.AI |
| Published | 10 June 2026 |
| Last updated at source | 10 June 2026 |
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