Proactive Knowledge Inquiry in Doctor-Patient Dialogue: Stateful Extraction, Belief Updating, and Path-Aware Action Planning
#proactive inquiry #doctor-patient dialogue #stateful extraction #belief updating #action planning #healthcare AI #medical diagnosis
📌 Key Takeaways
- The article introduces a framework for proactive knowledge inquiry in doctor-patient dialogues.
- It emphasizes stateful extraction to track conversation context and patient information over time.
- Belief updating is used to refine understanding based on new information during the dialogue.
- Path-aware action planning guides the inquiry process to optimize diagnostic or treatment paths.
- The approach aims to enhance medical dialogue systems for more efficient and accurate healthcare interactions.
📖 Full Retelling
arXiv:2603.17425v1 Announce Type: new
Abstract: Most automated electronic medical record (EMR) pipelines remain output-oriented: they transcribe, extract, and summarize after the consultation, but they do not explicitly model what is already known, what is still missing, which uncertainty matters most, or what question or recommendation should come next. We formulate doctor-patient dialogue as a proactive knowledge-inquiry problem under partial observability. The proposed framework combines sta
🏷️ Themes
Medical AI, Dialogue Systems
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Original Source
arXiv:2603.17425v1 Announce Type: new
Abstract: Most automated electronic medical record (EMR) pipelines remain output-oriented: they transcribe, extract, and summarize after the consultation, but they do not explicitly model what is already known, what is still missing, which uncertainty matters most, or what question or recommendation should come next. We formulate doctor-patient dialogue as a proactive knowledge-inquiry problem under partial observability. The proposed framework combines sta
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