Closed-Loop Validation-Repair for Healthcare Interoperability: A Multi-Model Study of Schema Compliance in Clinical LLMs
Healthcare interoperability requires AI systems to produce structured outputs conforming to standardized schemas including ICD-10 for diagnostic coding, CPT for procedure billing, and HL7 FHIR for data exchange. While large language models demonstrate clinical reasoning capabilities, their integration into electronic health record systems faces a critical barrier: schema noncompliance. We evaluate three open-source models, Qwen2.5 7B, Llama 3.1 8B, and Gemma2 9B, via local deployment across 320
Record details
Published: 27 July 2026
Source: arXiv cs.AI
Category: Research
Topics: Regulation · Healthcare
Retrieved: 28 July 2026
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How to cite this record
ethics.ai (27 July 2026), “Closed-Loop Validation-Repair for Healthcare Interoperability: A Multi-Model Study of Schema Compliance in Clinical LLMs,” evidence record 14053, https://ethics.ai/record/14053 (originally published by arXiv cs.AI).
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