Health Information Processing. Evaluation Track Papers

Shared task 1: Content Quality Control Task for Admission Records in Inpatient Electronic Medical Records.- Overview of the Content Quality Control Task for Admission Records in Inpatient Electronic Medical Records in CHIP 2025..- MedShard: Privacy-Preserving EMR QC with Rule Sharding and Multi-Agent Collaboration..- Dual Enhancement with In-Context Learning and Chain-ofThought: Large Language Model-Driven Intelligent Connotation Quality Control of Medical Records..- Semantic Quality Control of EMR Admission Notes: Integrating Rule Guidance, Prompt Optimization, and RAG.- Leveraging Phased Training and Multi-Granularity Prompting with Large Language Models for Few-Shot Quality Control of Electronic Medical Records.- M3-MedQC: A Method for Inherent Quality Control of Electronic Medical Records Based on Large Language Models and Multi-Granularity Evaluation.- Quality Control of Electronic Medical Records Content Based on Q-LoRA Fine-tuning and a Hybrid Model-Rule Approach.- Shared Task 2: Discharge Medication Recommendation for Metabolic Diseases Based on Chinese Electronic Health Records.- Overview of CHIP 2025 Shared Task 2: Discharge Medication Recommendation for Metabolic Diseases Based on Chinese Electronic Health Records.- Towards Discharge Medication Recommendation via Multi-Scale Model Training and Multi-Dimensional Feature Enhancement.- DP-EMR: A Chinese Medication Recommendation Method for Metabolic Diseases based on Two-stage Ensemble Learning.- LoRA-Fine-Tuned LLMs for Discharge Medication Recommendation on Chinese EHRs.- Multi-Format Fine-Tuning and Optimized Voting Ensemble for Robust Medication Recommendation in Chinese EMRs.- Shared Task 3: Medical NLP Code Generation with FHIR for Clinical Trial Screening.- Overview of Medical NLP Code Generation with FHIR for Clinical Trial Screening.- A Large Language Model-based System for Automatic Medical NLP Code Generation.- An Iterative Code Generation and Optimization Framework Based on Dynamic Few-Shot Learning for Medical Information Processing.- Prompt-Driven Program Synthesis for Clinical Trial Screening Criteria: From Natural Language to Executable FHIR Code Generation.