arXiv 2610.36325 Deploys Ontology Constraints in Multi-Agent Diagnosis Pipeline
The framework uses ontology grounding to enforce evidence-backed reasoning steps in multi-agent differential diagnosis. It addresses hallucination and opacity by constraining inference to curated relations and generating targeted clarification queries. The method also provides a pathway for correcting obsolete facts through ontology revision instead of model retraining.
The system decomposes diagnosis into iterative reasoning agents that query structured medical ontologies rather than relying on LLM pattern matching alone. Each agent maps symptoms and findings to predefined relations, generates follow-up questions for missing discriminative features, and produces traceable inference chains. Code release allows direct inspection of the grounding mechanism.
No benchmark scores appear in the submission. Claims of reduced hallucination rest on the logical constraint that inference cannot exit the ontology graph, yet the paper supplies no ablation against ungrounded baselines or inter-rater agreement metrics with clinicians. This leaves open whether the architecture improves accuracy or merely adds auditability layers.
The approach directly targets knowledge obsolescence: when new evidence contradicts stored relations, ontology updates propagate to all agents without retraining the underlying language models. This mirrors requirements for long-running clinical agents that must discard superseded associations while preserving traceability.
Operational deployment would require live integration with hospital EHR systems and version-controlled ontology releases, shifting maintenance burden from model fine-tuning to knowledge-base curation cycles measured in weeks rather than months.
Szomiu et al.: Public evaluation on MIMIC-IV discharge summaries will show at least 12% reduction in unsupported diagnoses versus single-agent GPT-4 baseline within nine months of code release.
Sources (2)
- [1]Primary Source(https://arxiv.org/abs/2610.36325)
- [2]Supporting Source(https://arxiv.org/abs/2305.09617)