MedRLM: Recursive Multimodal Health Intelligence for Long-Context Clinical Reasoning, Sensor-Guided Screening, Evidence-Grounded Decision Support, and Community-to-Tertiary Referral Optimization
- 类型:arxiv
- 标识:2606.20164
- 链接:http://arxiv.org/abs/2606.20164v1
- 主分类:multimodal
- 形态:method
- 被引:0
- 被引来源:Semantic Scholar + OpenAlex
- S2被引:0
- OpenAlex被引:0
- 影响力被引:0
- TLDR:MedRLM aims to move medical AI from static question answering toward auditable, multimodal, and workflow-aware clinical decision support, and introduces a Clinical Evidence Graph Memory to connect patient-specific observations with retrieved evidence.
- OpenAlex ID:W7165400151
- OpenAlex DOI:10.48550/arxiv.2606.20164
- DOI:10.48550/arxiv.2606.20164
- DOI来源:OpenAlex
- 开放获取:green
- 开放获取链接:https://doi.org/10.48550/arxiv.2606.20164
- OpenAlex更新:2026-07-19
- 副分类:rag
- 待LLM分类:否
- 标题中文:MedRLM:用于长上下文临床推理、传感器引导筛查、循证决策支持和社区到三级转诊优化的递归多模态健康智能
- TLDR中文:MedRLM 旨在将医疗 AI 从静态问答转向可审计、多模态且工作流感知的临床决策支持,并引入临床证据图记忆,将患者特定观察与检索到的证据相连接。
- 来源文件:
- /inbox/tom/_candidates/2026-06-22-agent-rag-longcontext-candidates.json
- /inbox/tom/_candidates/2026-06-21-agent-rag-longcontext-candidates.json
- /inbox/tom/_candidates/2026-06-20-agent-rag-longcontext-candidates.json
- /inbox/tom/_candidates/2026-06-19-agent-rag-longcontext-candidates.json
- [S2 enrich]
- [OpenAlex backfill]