The paper introduces CoRPS-Dial, a dual-agent framework that synthesizes pre‑consultation medical dialogues by combining a persona‑driven patient agent with a process‑guided doctor agent. It incorporates post‑hoc quality control to ensure role consistency, workflow completeness, and textual consistency. Experiments on coronary heart disease data show that CoRPS‑Dial produces dialogues that better match real conversations in information coverage, clinical compliance, and naturalness, and that the synthetic data improves downstream medical dialogue tasks.
arXiv:2603. 25821v3 Announce Type: replace-cross Abstract: We present Doctorina MedBench, an evaluation framework for agent-based medical AI based on the simulation of physician-patient interactions.
arXiv:2606. 08938v1 Announce Type: cross Abstract: Clinical diagnosis requires flexible use of multiple reasoning paradigms under incomplete patient information.
arXiv:2608. 13476v1 Announce Type: new Abstract: We present Multi-Agent Reasoning and Coordination (MARC), an open-source framework that replaces monolithic LLM prompting with deterministic multi-agent orchestration for clinical reasoning.
arXiv:2606. 30491v1 Announce Type: cross Abstract: Background.
arXiv:2603. 25821v2 Announce Type: replace-cross Abstract: We present Doctorina MedBench, a comprehensive evaluation framework for agent-based medical AI based on the simulation of realistic physician-patient interactions.
arXiv:2602.01995v2 Announce Type: replace Abstract: Conversational diagnosis requires multi-turn history-taking, where an agent asks clarifying questions to refine differential diagnoses under incomp...
ClinAgent is a conversational system that uses a ReAct-based LLM agent to retrieve and synthesize clinical trial information from multiple sources such as ClinicalTrials.gov, PubMed, and a local dataset. The agent iteratively reasons over user queries, selects appropriate tools, and refines its actions to provide grounded, up-to-date responses in natural language across multi-turn interactions. Evaluation across three phases shows that DeepSeek (thinking mode) excels in planning quality while Gemini 3.0 Flash delivers the highest overall performance and expert ratings, demonstrating the promise of agentic AI for improving clinical trial data access.
arXiv:2608.16053v2 Announce Type: replace Abstract: Synthetic conversational speech has become an important resource for developing and evaluating conversational speech systems. However, existing dia...
arXiv:2508. 01401v2 Announce Type: replace-cross Abstract: Physicians spend significant time documenting clinical encounters, a burden that contributes to professional burnout.
MedConceal is a new benchmark for evaluating medical dialogue systems on hidden‑concern reasoning under partial observability. It features 300 curated cases and 600 clinician‑LLM interactions, using an interactive patient simulator that hides latent concerns and tracks their revelation and resolution through theory‑grounded communication signals. The benchmark assesses both confirmation (surfacing hidden concerns) and intervention (addressing the primary concern), revealing that current models excel on different metrics while human clinicians still outperform them on intervention success.
arXiv:2608.24327v2 Announce Type: replace Abstract: With the advent of Large Language Models and its instruction following capabilities a promising application is the task of summarization. Within th...
arXiv:2607. 08625v1 Announce Type: new Abstract: Consumer-facing health chatbots powered by large language models (LLMs) are increasingly used for symptom assessment.