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LLM-Based Multi-Agent Systems for Clinical Workflows: A Survey of AI Hospitals

Paper · 2026 · Zonghai Yao and Hong yu

Summary

This ACL 2026 survey asks how LLM-based multi-agent systems for healthcare should be described, compared, and judged ready for real clinical use. The authors note a mismatch: models score well on benchmarks, but there is little evidence that these gains carry over to actual hospital workflows. They define an "AI hospital" narrowly as a system with four properties: agents hold explicit roles, pass a shared case state between care stages, rely on tools grounded in EHRs or guidelines, and run under safety gates with audit-ready logs. Single-agent chatbots and one-turn QA systems fall outside this scope.

The paper's unit of analysis is the workflow state transition. It uses a triage → consultation → discharge example to organize prior work along three axes:

  • roles and handoffs,
  • memory, evidence, and tools,
  • reasoning, control, and escalation.

On top of this taxonomy, it proposes an evaluation framework, a staged readiness scale, and a catalogue of recurring failure modes. The survey contributes no new dataset or model. Its value is a common reporting and gating protocol that ties deployment claims to measurable workflow evidence.

Key points

  • Recurring questions: Every step is analyzed by who owns the next action, which state must survive the handoff, what evidence justifies the step, and which gate can block or escalate it.
  • Four-layer evaluation stack: safety, process, outcome, and operations. Operations covers measures such as latency tails, tokens per case, and the number of human interventions.
  • Integration Readiness Levels (IRL1–IRL6): a staged deployment scale paired with task-level logging requirements. The authors present the thresholds as adjustable governance templates rather than fixed constants.
  • Failure roadmap (Table 5): recurring problems include weak or ungated escalation, untraceable action chains (e.g., EHR or FHIR calls that lose provenance), drift, jailbreaks, and cost shocks. Each failure is linked to a minimal test, a required log bundle, and the IRL stages it should block.
  • Coverage: ACL, NeurIPS, ICLR, ICML, AAAI, selected medical journals, and preprints from arXiv, medRxiv, and bioRxiv.

Our summary of the paper, in our own words — not its text. The work belongs to its authors; read it at the links above.

 Institutions

🎓University of Massachusetts AmherstAmherst Center · United States114 works · 68,731 citations🎓University of Massachusetts LowellLowell · United States16 works · 3,942 citations

Also on the byline: Bedford Hospital.

 Fields, topics and concepts

📚 Shelves 6The field of science this work belongs to (OpenAlex fields).Computer Science · 18,614 worksArtificial Intelligence · 17,965 worksMedicine · 275 worksHealth Informatics · 214 worksHealth Professions · 75 worksHealth Information Management · 56 works

Cite

Cite as Zonghai Yao and Hong yu. 2026. LLM-Based Multi-Agent Systems for Clinical Workflows: A Survey of AI Hospitals. Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers).

The paper itself, not this page. BibTeX from the library's record of the work. DOI 10.18653/v1/2026.acl-long.2123

@inproceedings{yao2026llm,
  title = {{LLM-Based Multi-Agent Systems for Clinical Workflows: A Survey of AI Hospitals}},
  author = {Zonghai Yao and Hong yu},
  booktitle = {Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)},
  year = {2026},
  doi = {10.18653/v1/2026.acl-long.2123},
  url = {https://doi.org/10.18653/v1/2026.acl-long.2123}
}

References

104 references, 13 of them with a card of ours. ↗ leads to the work, «find» searches for one we have no id for yet.

  1. Mahyar Abbasian, Iman Azimi, Amir M Rahmani, and Ramesh Jain. 2025. Conversational health agents: a personalized large language model-powered agent framework. JAMIA open, 8(4):ooaf067. find
  2. Julián N. Acosta, Guido J. Falcone, Pranav Rajpurkar, and Eric J. Topol. 2022. Multimodal biomedical ai. Nature Medicine, 28:1773 – 1784. find
  3. Monica Agrawal, Irene Y Chen, Freya Gulamali, and Shalmali Joshi. 2025. The evaluation illusion of large language models in medicine. npj Digital Medicine, 8(1):600. find
  4. Rahul K Arora, Jason Wei, Rebecca Soskin Hicks, Preston Bowman, Joaquin Quiñonero-Candela, Foivos Tsimpourlas, Michael Sharman, Meghan Shah, Andrea Vallone, Alex Beutel, et al. 2025. Healthbench: Evaluating large language models towards improved human health. arXiv preprint arXiv:2505.08775.
  5. Mohammad Asadi, Jack W O’Sullivan, Fang Cao, Tahoura Nedaee, Kamyar Fardi, Fei-Fei Li, Ehsan Adeli, and Euan Ashley. 2026. Mirage the illusion of visual understanding. arXiv preprint arXiv:2603.21687. — [arXiv:2603.21687](https://arxiv.org/abs/2603.21687) find
  6. Zhijie Bao, Qingyun Liu, Ying Guo, Zhengqiang Ye, Jun Shen, Shirong Xie, Jiajie Peng, Xuanjing Huang, and Zhongyu Wei. 2024. Piors: Personalized intelligent outpatient reception based on large language model with multi-agents medical scenario simulation. arXiv preprint arXiv:2411.13902. — [arXiv:2411.13902](https://arxiv.org/abs/2411.13902) find
  7. Andrew M Bean, Rebecca Elizabeth Payne, Guy Parsons, Hannah Rose Kirk, Juan Ciro, Rafael Mosquera-Gómez, Sara Hincapié M, Aruna S Ekanayaka, Lionel Tarassenko, Luc Rocher, et al. 2026. Reliability of llms as medical assistants for the general public: a randomized preregistered study. Nature Medicine… find
  8. Suhana Bedi, Hejie Cui, Miguel Fuentes, Alyssa Unell, Michael Wornow, Juan M Banda, Nikesh Kotecha, Timothy Keyes, Yifan Mai, Mert Oez, et al. 2026. Holistic evaluation of large language models for medical tasks with medhelm. Nature Medicine, pages 1–9. find
  9. Suhana Bedi, Yixing Jiang, Philip Chung, Sanmi Koyejo, and Nigam Shah. 2025a. Fidelity of medical reasoning in large language models. JAMA Network Open, 8(8):e2526021. find
  10. Suhana Bedi, Yutong Liu, Lucy Orr-Ewing, Dev Dash, Sanmi Koyejo, Alison Callahan, Jason A Fries, Michael Wornow, Akshay Swaminathan, Lisa Soleymani Lehmann, et al. 2025b. Testing and evaluation of health care applications of large language models: a systematic review. Jama, 333(4):319–328. find
  11. Pengshan Cai, Zonghai Yao, Fei Liu, Dakuo Wang, Meghan Reilly, Huixue Zhou, Lingxi Li, Yi Cao, Alok Kapoor, Adarsha Bajracharya, et al. 2023. Paniniqa: Enhancing patient education through interactive question answering. Transactions of the Association for Computational Linguistics, 11:1518– 1536.
  12. Junying Chen, Chi Gui, Anningzhe Gao, Ke Ji, Xidong Wang, Xiang Wan, and Benyou Wang. 2025a. Cod, towards an interpretable medical agent using chain of diagnosis. In Findings of the Association for Computational Linguistics: ACL 2025, pages 14345–14368. find
  13. Junying Chen, Chi Gui, Anningzhe Gao, Ke Ji, Xidong Wang, Xiang Wan, and Benyou Wang. 2025b. Cod, towards an interpretable medical agent using chain of diagnosis. In Findings of the Association for Computational Linguistics: ACL 2025, pages 14345–14368. find
  14. Siyuan Chen, Mengyue Wu, Kenny Q Zhu, Kunyao Lan, Zhiling Zhang, and Lyuchun Cui. 2023. Llm-empowered chatbots for psychiatrist and patient simulation: application and evaluation. arXiv preprint arXiv:2305.13614. — [arXiv:2305.13614](https://arxiv.org/abs/2305.13614) find
  15. Xi Chen, Huahui Yi, Mingke You, WeiZhi Liu, Li Wang, Hairui Li, Xue Zhang, Yingman Guo, Lei Fan, Gang Chen, et al. 2025c. Enhancing diagnostic capability with multi-agents conversational large language models. NPJ digital medicine, 8(1):159. find
  16. Xi Chen, Huahui Yi, Mingke You, WeiZhi Liu, Li Wang, Hairui Li, Xue Zhang, Yingman Guo, Lei Fan, Gang Chen, et al. 2025d. Enhancing diagnostic capability with multi-agents conversational large language models. NPJ digital medicine, 8(1):159. find
  17. Xuanzhong Chen, Ye Jin, Xiaohao Mao, Lun Wang, Shuyang Zhang, and Ting Chen. 2026. Rareagents: Autonomous multi-disciplinary team for rare disease diagnosis and treatment. Proceedings of the AAAI Conference on Artificial Intelligence, 40(1):101–109. find
  18. Zhuoyun Du, LujieZheng LujieZheng, Renjun Hu, Yuyang Xu, Xiawei Li, Ying Sun, Wei Chen, Jian Wu, Haolei Cai, and Haochao Ying. 2025. Llms can simulate standardized patients via agent coevolution. Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long…
  19. Rahma Elkamouchi, Abdelaziz Daaif, and Kamal Elguemmat. 2024. Multi-agents system in healthcare: A systematic literature review. In International Conference on Smart Applications and Data Analysis, pages 200–214. Springer. find
  20. Ethan Goh, Robert J Gallo, Eric Strong, Yingjie Weng, Hannah Kerman, Jason A Freed, Joséphine A Cool, Zahir Kanjee, Kathleen P Lane, Andrew S Parsons, et al. 2025. Gpt-4 assistance for improvement of physician performance on patient care tasks: a randomized controlled trial. Nature Medicine, 31(4):1… find
  21. Alex J Goodell, Simon N Chu, Dara Rouholiman, and Larry F Chu. 2025. Large language model agents can use tools to perform clinical calculations. npj Digital Medicine, 8(1):163. find
  22. Shengxin Hong, Liang Xiao, Xin Zhang, and Jianxia Chen. 2024. Argmed-agents: Explainable clinical decision reasoning with llm disscusion via argumentation schemes. In 2024 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), pages 5486–5493. IEEE. find
  23. Won Seok Jang, Hieu Tran, Manav Mistry, SaiKiran Gandluri, Yifan Zhang, Sharmin Sultana, Sunjae Kwon, Yuan Zhang, Zonghai Yao, and Hong Yu. 2025. Chatbot to help patients understand their health. In Proceedings of the Conference on Empirical Methods in Natural Language Processing. Conference on Empi… find
  24. Yixing Jiang, Kameron C Black, Gloria Geng, Danny Park, James Zou, Andrew Y Ng, and Jonathan H Chen. 2025. Medagentbench: a virtual ehr environment to benchmark medical llm agents. Nejm Ai, 2(9):AIdbp2500144. find
  25. Qiao Jin, Yifan Yang, Qingyu Chen, and Zhiyong Lu. 2024. Genegpt: augmenting large language models with domain tools for improved access to biomedical information. Bioinformatics, 40(2):btae075.
  26. Adibvafa Fallahpour, Jun Ma, Alif Munim, Hongwei Lyu, and Bo Wang. 2025. Medrax: Medical reasoning agent for chest x-ray. In International Conference on Machine Learning, pages 15661–15676. PMLR. find
  27. Shreya Johri, Jaehwan Jeong, Benjamin A Tran, Daniel I Schlessinger, Shannon Wongvibulsin, Leandra A Barnes, Hong-Yu Zhou, Zhuo Ran Cai, Eliezer M Van Allen, David Kim, et al. 2025. An evaluation framework for clinical use of large language models in patient interaction tasks. Nature medicine, 31(1)… find
  28. Zhihao Fan, Lai Wei, Jialong Tang, Wei Chen, Wang Siyuan, Zhongyu Wei, and Fei Huang. 2025. Ai hospital: Benchmarking large language models in a multi-agent medical interaction simulator. Proceedings of the 31st International Conference on Computational Linguistics, pages 10183–10213.
  29. Shreya Johri, Jaehwan Jeong, Benjamin A Tran, Daniel I Schlessinger, Shannon Wongvibulsin, Zhuo Ran Cai, Roxana Daneshjou, and Pranav Rajpurkar. 2023. Guidelines for rigorous evaluation of clinical llms for conversational reasoning. medRxiv, pages 2023– 09. find
  30. Giacomo Frisoni, Alessio Cocchieri, Alex Presepi, Gianluca Moro, and Zaiqiao Meng. 2024. To generate or to retrieve? on the effectiveness of artificial contexts for medical open-domain question answering. In Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Vol… find
  31. Yuhe Ke, Rui Yang, Sui An Lie, Taylor Xin Yi Lim, Yilin Ning, Irene Li, Hairil Rizal Abdullah, Daniel Shu Wei Ting, and Nan Liu. 2024. Mitigating cognitive biases in clinical decision-making through multi-agent conversations using large language models: simulation study. Journal of Medical Internet… find
  32. Mauro Giuffré and Dennis L. Shung. 2023. Harnessing the power of synthetic data in healthcare: innovation, application, and privacy. NPJ Digital Medicine, 6. find
  33. Yubin Kim, Chanwoo Park, Hyewon Jeong, Yik S Chan, Xuhai Xu, Daniel McDuff, Hyeonhoon Lee, Marzyeh Ghassemi, Cynthia Breazeal, and Hae W Park. 2024. find
  34. Mdagents: An adaptive collaboration of llms for medical decision-making. Advances in Neural Information Processing Systems, 37:79410–79452. find
  35. Sunjae Kwon, Zonghai Yao, Harmon S Jordan, David A Levy, Brian Corner, and Hong Yu. 2022. Medjex: A medical jargon extraction model with wiki’s hyperlink span and contextualized masked language model score. In Proceedings of the Conference on Empirical Methods in Natural Language Processing. Confere… find
  36. Yunghwei Lai, Kaiming Liu, Ziyue Wang, Weizhi Ma, and Yang Liu. 2025. Doctor-r1: Mastering clinical inquiry with experiential agentic reinforcement learning. arXiv preprint arXiv:2510.04284. — [arXiv:2510.04284](https://arxiv.org/abs/2510.04284) find
  37. Moustafa Laymouna, Yuanchao Ma, David Lessard, Tibor Schuster, Kim Engler, and Bertrand Lebouché. 2024. Roles, users, benefits, and limitations of chatbots in health care: rapid review. Journal of medical Internet research, 26:e56930. find
  38. Tyler Alise Le, Arpi Jivalagian, Tasneem Hiba, Joshua Franz, Shahab Ahmadzadeh, Treniece Eubanks, Leisa Oglesby, Sahar Shekoohi, Elyse M Cornett, and Alan D Kaye. 2023. Multi-agent systems and cancer pain management. Current Pain and Headache Reports, 27(9):379–386. find
  39. Binbin Li, Tianxin Meng, Xiaoming Shi, Jie Zhai, and Tong Ruan. 2023. Meddm: Llm-executable clinical guidance tree for clinical decision-making. arXiv preprint arXiv:2312.02441. — [arXiv:2312.02441](https://arxiv.org/abs/2312.02441) find
  40. Binxu Li, Tiankai Yan, Yuanting Pan, Jie Luo, Ruiyang Ji, Jiayuan Ding, Zhe Xu, Shilong Liu, Haoyu Dong, Zihao Lin, et al. 2024a. Mmedagent: Learning to use medical tools with multi-modal agent. In Findings of the Association for Computational Linguistics: EMNLP 2024, pages 8745–8760. find
  41. Junkai Li, Yunghwei Lai, Weitao Li, Jingyi Ren, Meng Zhang, Xinhui Kang, Siyu Wang, Peng Li, Ya-Qin Zhang, Weizhi Ma, et al. 2024b. Agent hospital: A simulacrum of hospital with evolvable medical agents. arXiv preprint arXiv:2405.02957. — [arXiv:2405.02957](https://arxiv.org/abs/2405.02957) find
  42. Shuyue S Li, Vidhisha Balachandran, Shangbin Feng, Jonathan S Ilgen, Emma Pierson, Pang W Koh, and Yulia Tsvetkov. 2024c. Mediq: Question-asking llms and a benchmark for reliable interactive clinical reasoning. Advances in Neural Information Processing Systems, 37:28858–28888.
  43. Jung Hoon Lim, Sunjae Kwon, Zonghai Yao, John P Lalor, and Hong Yu. 2024. Large language model-based role-playing for personalized medical jargon extraction. arXiv preprint arXiv:2408.05555. — [arXiv:2408.05555](https://arxiv.org/abs/2408.05555) find
  44. Jie Liu, Wenxuan Wang, Zizhan Ma, Guolin Huang, SU Yihang, Kao-Jung Chang, Haoliang Li, Linlin Shen, Michael Lyu, and Wenting Chen. 2025a. Medchain: Bridging the gap between llm agents and clinical practice with interactive sequence. In The Thirty-ninth Annual Conference on Neural Information Proces… find
  45. Qicai Liu, Zhichao Hu, Tao Huang, Yupeng Niu, Xinche Zhang, Shanwu Ma, Chutong Lin, Goh Kim Huat, Hyeokkoo Eric Kwon, Feng Gao, et al. 2026. Evomdt: a self-evolving multi-agent system for structured clinical decision-making in multi-cancer. npj Digital Medicine. find
  46. Sizhe Liu, Yizhou Lu, Siyu Chen, Xiyang Hu, Jieyu Zhao, Tianfan Fu, and Yue Zhao. 2024. Drugagent: Automating ai-aided drug discovery programming through llm multi-agent collaboration. In 2nd AI4Research Workshop: Towards a Knowledge-grounded Scientific Research Lifecycle. find
  47. Xiaohong Liu, Hao Liu, Guoxing Yang, Zeyu Jiang, Shuguang Cui, Zhaoze Zhang, Huan Wang, Liyuan Tao, Yongchang Sun, Zhu Song, et al. 2025b. A generalist medical language model for disease diagnosis assistance. Nature medicine, 31(3):932–942. find
  48. Zhaocheng Liu, Quan Tu, Wen Ye, Yu Xiao, Zhishou Zhang, Hengfu Cui, Yalun Zhu, Qiang Ju, Shizheng Li, and Jian Xie. 2025c. Exploring the inquiry-diagnosis relationship with advanced patient simulators. arXiv preprint arXiv:2501.09484. — [arXiv:2501.09484](https://arxiv.org/abs/2501.09484) find
  49. Ryan Louie, Ananjan Nandi, William Fang, Cheng Chang, Emma Brunskill, and Diyi Yang. 2024. Roleplay-doh: Enabling domain-experts to create llm-simulated patients via eliciting and adhering to principles. Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing, pages 10…
  50. Meng Lu, Brandon Ho, Dennis Ren, and Xuan Wang. 2024. Triageagent: Towards better multi-agents collaborations for large language model-based clinical triage. In Findings of the Association for Computational Linguistics: EMNLP 2024, pages 5747–5764. find
  51. Yanzeng Li, Cheng Zeng, Jialun Zhong, Ruoyu Zhang, Minhao Zhang, and Lei Zou. 2024d. Leveraging large language model as simulated patients for clinical education. arXiv preprint arXiv:2404.13066. — [arXiv:2404.13066](https://arxiv.org/abs/2404.13066) find
  52. Sravanthi Machcha, Sushrita Yerra, Sahil Gupta, Aishwarya Sahoo, Sharmin Sultana, Hong Yu, and Zonghai Yao. 2026. Knowing when to abstain: Medical LLMs under clinical uncertainty. In Proceedings of the 19th Conference of the European Chapter of the Association for Computational Linguistics (Volume 1…
  53. Yusheng Liao, Yutong Meng, Yuhao Wang, Hongcheng Liu, Yanfeng Wang, and Yu Wang. 2024. Automatic interactive evaluation for large language models with state aware patient simulator. arXiv preprint arXiv:2403.08495. — [arXiv:2403.08495](https://arxiv.org/abs/2403.08495) find
  54. Nikita Mehandru, Brenda Y Miao, Eduardo Rodriguez Almaraz, Madhumita Sushil, Atul Janardhan Butte, and Ahmed Alaa. 2024. Evaluating large language models as agents in the clinic. NPJ Digital Medicine, 7. find
  55. Prakamya Mishra, Zonghai Yao, Parth Vashisht, Feiyun Ouyang, Beining Wang, Vidhi Dhaval Mody, and Hong Yu. 2024. Synfac-edit: Synthetic imitation edit feedback for factual alignment in clinical summarization. Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing, pag… find
  56. Huachuan Qiu and Zhenzhong Lan. 2024. Interactive agents: Simulating counselor-client psychological counseling via role-playing llm-to-llm interactions. arXiv preprint arXiv:2408.15787.
  57. Daniel Philip Rose, Chia-Chien Hung, Marco Lepri, Israa Alqassem, Kiril Gashteovski, and Carolin Lawrence. 2025. Meddxagent: A unified modular agent framework for explainable automatic differential diagnosis. In Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics… find
  58. Samuel Schmidgall, Rojin Ziaei, Carl Harris, Eduardo Reis, Jeffrey Jopling, and Michael Moor. 2024. Agentclinic: a multimodal agent benchmark to evaluate ai in simulated clinical environments. arXiv preprint arXiv:2405.07960. — [arXiv:2405.07960](https://arxiv.org/abs/2405.07960) find
  59. Hanwen Shi, Jin Zhang, and Kunpeng Zhang. 2024a. Enhancing clinical trial patient matching through knowledge augmentation with multi-agents. arXiv preprint arXiv:2411.14637. — [arXiv:2411.14637](https://arxiv.org/abs/2411.14637) find
  60. Wenqi Shi, Ran Xu, Yuchen Zhuang, Yue Yu, Jieyu Zhang, Hang Wu, Yuanda Zhu, Joyce C Ho, Carl Yang, and May Dongmei Wang. 2024b. Ehragent: Code empowers large language models for few-shot complex tabular reasoning on electronic health records. In Proceedings of the 2024 Conference on Empirical Method… find
  61. Andries Petrus Smit, Nathan Grinsztajn, Paul Duckworth, Thomas D Barrett, and Arnu Pretorius. 2024. Should we be going mad? a look at multi-agent debate strategies for llms. In International Conference on Machine Learning, pages 45883–45905. PMLR. find
  62. Kyle Swanson, Wesley Wu, Nash L Bulaong, John E Pak, and James Zou. 2025. The virtual lab of ai agents designs new sars-cov-2 nanobodies. Nature, 646(8085):716–723. find
  63. Xiangru Tang, Anni Zou, Zhuosheng Zhang, Ziming Li, Yilun Zhao, Xingyao Zhang, Arman Cohan, and Mark Gerstein. 2024. Medagents: Large language models as collaborators for zero-shot medical reasoning. Findings of the Association for Computational Linguistics: ACL 2024, pages 599–621.
  64. Xinge Tao, Shuya Zhou, Kai Ding, Sairan Li, Yanzeng Li, Boyou Wu, Qirui Huang, Wangyue Chen, Muzi Shen, En Meng, et al. 2026. An llm chatbot to facilitate primary-to-specialist care transitions: a randomized controlled trial. Nature Medicine, pages 1–9. find
  65. Muhammad Usman Tariq. 2024. Multi-agent models in healthcare system design. In Bioethics of Cognitive Ergonomics and Digital Transition, pages 143–170. IGI Global. find
  66. Hieu Tran, Zonghai Yao, Nguyen Luong Tran, Zhichao Yang, Feiyun Ouyang, Shuo Han, Razieh Rahimi, and Hong Yu. 2026. Prime: Planning and retrieval-integrated memory for enhanced reasoning. In Proceedings of the AAAI Conference on Artificial Intelligence, volume 40, pages 33268–33276. find
  67. Hieu Tran, Zonghai Yao, Zhichao Yang, Junda Wang, Yifan Zhang, Shuo Han, Feiyun Ouyang, and Hong Yu. 2025. Rare: Retrieval-augmented reasoning enhancement for large language models. Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), pages…
  68. Tao Tu, Mike Schaekermann, Anil Palepu, Khaled Saab, Jan Freyberg, Ryutaro Tanno, Amy Wang, Brenna Li, Mohamed Amin, Yong Cheng, et al. 2025. Towards conversational diagnostic artificial intelligence. Nature, 642(8067):442–450. find
  69. Haochun Wang, Sendong Zhao, Zewen Qiang, Nuwa Xi, Bing Qin, and Ting Liu. 2024a. Beyond direct diagnosis: Llm-based multi-specialist agent consultation for automatic diagnosis. arXiv preprint arXiv:2401.16107. — [arXiv:2401.16107](https://arxiv.org/abs/2401.16107) find
  70. Jiashuo Wang, Yang Xiao, Yanran Li, Changhe Song, Chunpu Xu, Chenhao Tan, and Wenjie Li. 2024b. Towards a client-centered assessment of llm therapists by client simulation. arXiv preprint arXiv:2406.12266. — [arXiv:2406.12266](https://arxiv.org/abs/2406.12266) find
  71. Junda Wang, Zonghai Tao, Hansi Zeng, Zhichao Yang, Hamed Zamani, and Hong Yu. 2026. Tarse: Test-time adaptation via retrieval of skills and experience for reasoning agents. arXiv preprint arXiv:2603.01241. — [arXiv:2603.01241](https://arxiv.org/abs/2603.01241) find
  72. Junda Wang, Zhichao Yang, Zonghai Yao, and Hong Yu. 2024c. Jmlr: Joint medical llm and retrieval training for enhancing reasoning and professional question answering capability. arXiv preprint arXiv:2402.17887. find
  73. Junda Wang, Zonghai Yao, Lingxi Li, Junhui Qian, Zhichao Yang, and Hong Yu. 2025a. Chatthero: An llm-supported chatbot for behavior change and therapeutic support in addiction recovery. arXiv preprint arXiv:2508.20996. — [arXiv:2508.20996](https://arxiv.org/abs/2508.20996) find
  74. Junda Wang, Zonghai Yao, Zhichao Yang, Huixue Zhou, Rumeng Li, Xun Wang, Yucheng Xu, and Hong Yu. 2024d. Notechat: a dataset of synthetic patient-physician conversations conditioned on clinical notes. In Findings of the Association for Computational Linguistics: ACL 2024, pages 15183–15201. find
  75. Ruiyi Wang, Stephanie Milani, Jamie Chiu, Jiayin Zhi, Shaun Eack, Travis Labrum, Samuel Murphy, Nev Jones, Kate Hardy, Hong Shen, et al. 2024e. Patient-psi: Using large language models to simulate patients for training mental health professionals. In Proceedings of the 2024 Conference on Empirical M… find
  76. Wenxuan Wang, Zizhan Ma, Zheng Wang, Chenghan Wu, Jiaming Ji, Wenting Chen, Xiang Li, and Yixuan Yuan. 2025b. A survey of llm-based agents in medicine: How far are we from baymax? Findings of the Association for Computational Linguistics: ACL 2025, pages 10345–10359. find
  77. Yue Wang, Tianfan Fu, Yinlong Xu, Zihan Ma, Hongxia Xu, Bang Du, Yingzhou Lu, Honghao Gao, Jian Wu, and Jintai Chen. 2024f. Twin-gpt: digital twins for clinical trials via large language model. ACM Transactions on Multimedia Computing, Communications and Applications. find
  78. Zifeng Wang, Benjamin Danek, Ziwei Yang, Zheng Chen, and Jimeng Sun. 2024g. Can large language models replace data scientists in biomedical research? arXiv preprint arXiv:2410.21591. — [arXiv:2410.21591](https://arxiv.org/abs/2410.21591) find
  79. Zixiang Wang, Yinghao Zhu, Huiya Zhao, Xiaochen Zheng, Dehao Sui, Tianlong Wang, Wen Tang, Yasha Wang, Ewen Harrison, Chengwei Pan, et al. 2025c. Colacare: Enhancing electronic health record modeling through large language model-driven multi-agent collaboration. Proceedings of the ACM on Web Confere… find
  80. Ziyue Wang, Junde Wu, Linghan Cai, Chang Han Low, Xihong Yang, Qiaxuan Li, and Yueming Jin. 2025d. Medagent-pro: Towards evidence-based multi-modal medical diagnosis via reasoning agentic workflow. In The Thirteenth International Conference on Learning Representations. find
  81. Hao Wei, Jianing Qiu, Haibao Yu, and Wu Yuan. 2024. Medco: Medical education copilots based on a multi-agent framework. In European Conference on Computer Vision, pages 119–135. Springer. find
  82. Ross Williams, Niyousha Hosseinichimeh, Aritra Majumdar, and Navid Ghaffarzadegan. 2023. Epidemic modeling with generative agents. arXiv preprint arXiv:2307.04986. — [arXiv:2307.04986](https://arxiv.org/abs/2307.04986) find
  83. Michael Wornow, Suhana Bedi, Miguel Angel Fuentes Hernandez, Ethan Steinberg, Jason Alan Fries, Christopher Re, Sanmi Koyejo, and Nigam Shah. 2025. Context clues: Evaluating long context models for clinical prediction tasks on ehr data. In The Thirteenth International Conference on Learning Represen… find
  84. Junde Wu, Jiayuan Zhu, Yunli Qi, Jingkun Chen, Min Xu, Filippo Menolascina, Yueming Jin, and Vicente Grau. 2025. Medical graph rag: Evidence-based medical large language model via graph retrieval-augmented generation. In Proceedings of the 63rd Annual Meeting of the Association for Computational Lin…
  85. Yuqi Wu, Guangya Wan, Jingjing Li, Shengming Zhao, Lingfeng Ma, Tianyi Ye, Mike Zhang, Ion Pop, Yanbo Zhang, and Jie Chen. 2026. Wisemind: a knowledge-guided multi-agent framework for accurate and empathetic psychiatric diagnosis. npj Digital Medicine. find
  86. Yihang Xiao, Jinyi Liu, YAN ZHENG, Shaoqing Jiao, Jianye HAO, Xiaohan Xie, Ruitao Wang, Fei Ni, Yuxiao Li, Zhen Wang, et al. 2025. Cellagent: Llm-driven multi-agent framework for natural language-based single-cell analysis. In The Fourteenth International Conference on Learning Representations. find
  87. Guangzhi Xiong, Qiao Jin, Xiao Wang, Yin Fang, Haolin Liu, Yifan Yang, Fangyuan Chen, Zhixing Song, Dengyu Wang, Minjia Zhang, et al. 2025. Rag-gym: Optimizing reasoning and search agents with process supervision. arXiv preprint arXiv:2502.13957. — [arXiv:2502.13957](https://arxiv.org/abs/2502.13957) find
  88. Weixiang Yan, Haitian Liu, Tengxiao Wu, Qian Chen, Wen Wang, Haoyuan Chai, and Jiayi Wang. 2025a. Clinicallab: Aligning agents for multi-departmental clinical diagnostics in the real world. In The Thirty-ninth Annual Conference on Neural Information Processing Systems Datasets and Benchmarks Track. find
  89. Weixiang Yan, Haitian Liu, Tengxiao Wu, Qian Chen, Wen Wang, Haoyuan Chai, and Jiayi Wang. 2025b. Clinicallab: Aligning agents for multi-departmental clinical diagnostics in the real world. The Thirty-ninth Annual Conference on Neural Information Processing Systems Datasets and Benchmarks Track. find
  90. Bufang Yang, Siyang Jiang, Lilin Xu, Kaiwei Liu, Hai Li, Guoliang Xing, Hongkai Chen, Xiaofan Jiang, and Zhenyu Yan. 2024. Drhouse: An llm-empowered diagnostic reasoning system through harnessing outcomes from sensor data and expert knowledge. Proceedings of the ACM on Interactive, Mobile, Wearable… find
  91. Dingkang Yang, Jinjie Wei, Mingcheng Li, Jiyao Liu, Lihao Liu, Ming Hu, Junjun He, Yakun Ju, Wei Zhou, Yang Liu, et al. 2025. Medaide: information fusion and anatomy of medical intents via llm-based agent collaboration. Information Fusion, page 103743. find
  92. Zonghai Yao, Talha Chafekar, Junda Wang, Shuo Han, Feiyun Ouyang, Junhui Qian, Lingxi Li, and Hong Yu. 2026a. Chatclids: Simulating persuasive ai dialogues to promote closed-loop insulin adoption in type 1 diabetes care. In Proceedings of the AAAI Conference on Artificial Intelligence, volume 40, pa… find
  93. Zonghai Yao, Nandyala Siddharth Kantu, Guanghao Wei, Hieu Tran, Zhangqi Duan, Sunjae Kwon, Zhichao Yang, and Hong Yu. 2024. Readme: Bridging medical jargon and lay understanding for patient education through data-centric nlp. Findings of the Association for Computational Linguistics: EMNLP 2024, pag… find
  94. Zonghai Yao, Benjamin Schloss, and Sai Selvaraj. 2023. Improving summarization with human edits. Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, pages 2604– 2620. find
  95. Shuang Zhou, Wenya Xie, Jiaxi Li, Zaifu Zhan, Meijia Song, Han Yang, Cheyenna Espinoza, Lindsay Welton, Xinnie Mai, Yanwei Jin, et al. 2025. Automating expert-level medical reasoning evaluation of large language models. npj Digital Medicine. find
  96. Zonghai Yao, Michael Sun, Won Seok Jang, Sunjae Kwon, Soie Kwon, and Hong Yu. 2025. Dischar-gesim: A simulation benchmark for educational doctor–patient communication at discharge. In Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing, pages 10783– 10809. find
  97. Yinghao Zhu, Ziyi He, Haoran Hu, Xiaochen Zheng, Xichen Zhang, Zixiang Wang, Junyi Gao, Liantao Ma, and Lequan Yu. 2025. Medagentboard: Benchmarking multi-agent collaboration with conventional methods for diverse medical tasks. In The Thirty-ninth Annual Conference on Neural Information Processing S… find
  98. Zonghai Yao, Zihao Zhang, Chaolong Tang, Xingyu Bian, Youxia Zhao, Zhichao Yang, Junda Wang, Huixue Zhou, Won Seok Jang, Feiyun Ouyang, and Hong Yu. 2026b. MedQA-CS: Objective structured clinical examination (OSCE)-style benchmark for evaluating LLM clinical skills. In Proceedings of the 19th Confer…
  99. Zonghai Yao, Youxia Zhao, Avijit Mitra, David A Levy, Emily Druhl, Jack Tsai, and Hong Yu. 2026c. Synthehr-eviction: enhancing eviction sdoh detection with llm-augmented synthetic ehr data. npj Digital Medicine. find
  100. Huizi Yu, Jiayan Zhou, Lingyao Li, Shan Chen, Jack Gallifant, Anye Shi, Jie Sun, Xiang Li, Jingxian He, Wenyue Hua, et al. 2025. Simulated patient systems powered by large language model-based ai agents offer potential for transforming medical education. Communications Medicine. find
  101. Ling Yue, Sixue Xing, Jintai Chen, and Tianfan Fu. 2024. Clinicalagent: Clinical trial multi-agent system with large language model-based reasoning. In Proceedings of the 15th ACM International Conference on Bioinformatics, Computational Biology and Health Informatics, pages 1–10. find
  102. Shengbin Yue, Siyuan Wang, Wei Chen, Xuanjing Huang, and Zhongyu Wei. 2025. Synergistic multi-agent framework with trajectory learning for knowledge-intensive tasks. Proceedings of the AAAI Conference on Artificial Intelligence, 39(24):25796– 25804. find
  103. Weike Zhao, Chaoyi Wu, Yanjie Fan, Pengcheng Qiu, Xiaoman Zhang, Yuze Sun, Xiao Zhou, Shuju Zhang, Yu Peng, Yanfeng Wang, et al. 2026. An agentic system for rare disease diagnosis with traceable reasoning. Nature, pages 1–10. find
  104. Yutian Zhao, Huimin Wang, Yefeng Zheng, and Xian Wu. 2025. A layered debating multi-agent system for similar disease diagnosis. In Proceedings of the 2025 Conference of the Nations of the Americas Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 2: Short… find

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