SynDocDis generates synthetic physician-to-physician dialogues from metadata using LLMs and achieves high physician-rated quality in oncology and hepatology scenarios.
npj Digital Medicine7, 20 (1 2024)
2 Pith papers cite this work. Polarity classification is still indexing.
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The system integrates a Neo4j knowledge graph, four-stage symptom matching with LLM verification, genetic-algorithm-optimized proactive questioning, and multimodal evidence-based visualizations to improve diagnostic transparency and treatment interpretability in TCM, reporting 32% fewer non-standard
citing papers explorer
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SynDocDis: A Metadata-Driven Framework for Generating Synthetic Physician Discussions Using Large Language Models
SynDocDis generates synthetic physician-to-physician dialogues from metadata using LLMs and achieves high physician-rated quality in oncology and hepatology scenarios.
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Evidence-Based Intelligent Diagnostic and Therapeutic Visualization System with Large Language Models: Multi-Turn Interaction and Multimodal Treatment Plan Generation
The system integrates a Neo4j knowledge graph, four-stage symptom matching with LLM verification, genetic-algorithm-optimized proactive questioning, and multimodal evidence-based visualizations to improve diagnostic transparency and treatment interpretability in TCM, reporting 32% fewer non-standard