Tag
ChatHealthAI is a multimodal reasoning framework that aligns structured EHR representations with a frozen LLM to enable grounded clinical reasoning while maintaining predictive performance.
MedGuideX transforms clinical practice guidelines into executable decision logic to generate factual and counterfactual QA data for training medical LLMs, achieving a 10.28% relative improvement in average accuracy across clinical reasoning benchmarks.
SEMA-RAG is a self-evolving multi-agent RAG framework for medical question answering that decouples interpretation, exploration, and adjudication into three specialist agents, achieving significant accuracy improvements over baselines across multiple benchmarks.
ClinSeekAgent is an automated agentic framework that enables large language models to actively acquire and synthesize multimodal clinical evidence from raw data sources, improving decision-making accuracy in both text-only and multimodal tasks. It introduces the ClinSeek-Bench benchmark and a distilled model ClinSeek-35B-A3B that achieves strong performance on agentic clinical reasoning.
This paper introduces Checkup2Action, a multimodal dataset and benchmark for generating patient-oriented action cards from clinical check-up reports, addressing the interpretability gap for laypersons.