mlsanityData to 14 Oct 2026

DynamiCare: A Dynamic Multi-Agent Framework for Interactive and Open-Ended Medical Decision-Making

arXiv 2507.02616 ↗First posted 3 Jul 2025cs.AIcited by 2

On the map: LLM agents and tool use → Medical and scientific domain agents

Abstract (arXiv)

The rise of Large Language Models (LLMs) has enabled the development of specialized AI agents with domain-specific reasoning and interaction capabilities, particularly in healthcare. While recent frameworks simulate medical decision-making, they largely focus on single-turn tasks where a doctor agent receives full case information upfront -- diverging from the real-world diagnostic process, which is inherently uncertain, interactive, and iterative. In this paper, we introduce MIMIC-Patient, a structured dataset built from the MIMIC-III electronic health records (EHRs), designed to support dynamic, patient-level simulations. Building on this, we propose DynamiCare, a novel dynamic multi-agent framework that models clinical diagnosis as a multi-round, interactive loop, where a team of specialist agents iteratively queries the patient system, integrates new information, and dynamically adapts its composition and strategy. We demonstrate the feasibility and effectiveness of DynamiCare through extensive experiments, establishing the first benchmark for dynamic clinical decision-making with LLM-powered agents.

Key facts. Cited by 2 papers in the map (data through 14 Oct 2026). Placed in Medical and scientific domain agents, one of 16 directions in LLM agents and tool use. Builds on 19 of its 41 references that are in the map. First posted on arXiv 3 Jul 2025.

Builds on

19 of 41 references.

Closest ancestors · 2

Same direction, newest first

  1. 2024AgentClinic: a multimodal agent benchmark to evaluate AI in simulated clinical environments13 May
  2. 2024AgentMD: Empowering Language Agents for Risk Prediction with Large-Scale Clinical Tool Learning20 Feb

Other references · 17

  1. 2022Self-Consistency Improves Chain of Thought Reasoning in Language Modelscited by 5,708
  2. 2023A Survey on Large Language Model based Autonomous Agentscited by 2,242
  3. 2023AutoGen: Enabling Next-Gen LLM Applications via Multi-Agent Conversationcited by 1,988
  4. 2022Large Language Models Encode Clinical Knowledgecited by 1,830
  5. 2023Improving Factuality and Reasoning in Language Models through Multiagent Debatecited by 1,784
  6. 2020What Disease does this Patient Have? A Large-scale Open Domain Question Answering Dataset from Medical Examscited by 1,356
  7. 2019PubMedQA: A Dataset for Biomedical Research Question Answeringcited by 1,288
  8. 2023Encouraging Divergent Thinking in Large Language Models through Multi-Agent Debatecited by 1,011
  9. 2023Capabilities of GPT-4 on Medical Challenge Problemscited by 638
  10. 2023MedAgents: Large Language Models as Collaborators for Zero-shot Medical Reasoningcited by 316
  11. 2023ReConcile: Round-Table Conference Improves Reasoning via Consensus among Diverse LLMscited by 309
  12. 2018Scalable and accurate deep learning for electronic health recordscited by 280
5 more
  1. 2024Capabilities of Gemini Models in Medicinecited by 237
  2. 2024MediQ: Question-Asking LLMs and a Benchmark for Reliable Interactive Clinical Reasoningcited by 154
  3. 2018emrQA: A Large Corpus for Question Answering on Electronic Medical Recordscited by 135
  4. 2024Benchmarking Large Language Models on Answering and Explaining Challenging Medical Questionscited by 109
  5. 2024EHRNoteQA: An LLM Benchmark for Real-World Clinical Practice Using Discharge Summariescited by 35

Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2026: 2.

2 papers.

  1. 2026A Survey of Agentic Reasoning for Large Language Models: Towards Recursively Self-Improving and Collective Agentscited by 50
  2. 2026Examining the Vulnerability of Multi-Agent Medical Systems to Human Interventions for Clinical Reasoningcited by 0

Similar, not cited

Close in wording, no citation either way

  1. 2025Empowering Medical Multi-Agents with Clinical Consultation Flow for Dynamic Diagnosis
  2. 2026MeDxAgent: Multi-Agent Consultation for Interactive Medical Diagnosis
  3. 2024AI Hospital: Benchmarking Large Language Models in a Multi-agent Medical Interaction Simulator
  4. 2024Adaptive Reasoning and Acting in Medical Language Agents
  5. 2026ClinicalAgents: Multi-Agent Orchestration for Clinical Decision Making with Dual-Memory
  6. 2025A Knowledge-driven Adaptive Collaboration of LLMs for Enhancing Medical Decision-making
  7. 2026EMR: Self-Evolving Medical Multi-Agent System via Experience Mining and Reuse
  8. 2025ClinDEF: A Dynamic Evaluation Framework for Large Language Models in Clinical Reasoning