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The rapid advancement of Large Language Models (LLMs) has stimulated interest in multi-agent collaboration for addressing complex medical tasks.
ROUGE: A package for automatic evaluation of summaries
Chin-Yew Lin · 2004
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Lay summaries needed to enhance science communication
Lauren M Kuehne and Julian D Olden · 2015
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Optimizing statistical machine translation for text simplification
Wei Xu, Courtney Napoles, Ellie Pavlick, Quanze Chen, and Chris Callison-Burch · 2016
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Xgboost: A scalable tree boosting system
Tianqi Chen and Carlos Guestrin · 2016
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Decoupled weight decay regularization
Ilya Loshchilov and Frank Hutter · 2017
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A dataset of clinically generated visual questions and answers about radiology images
Jason J Lau, Soumya Gayen, Asma Ben Abacha, and Dina Demner-Fushman · 2018
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Benchmarking deep learning models on large healthcare datasets
Sanjay Purushotham, Chuizheng Meng, Zhengping Che, and Yan Liu · 2018
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Artificial intelligence and machine learning in clinical development: a translational perspective
Pratik Shah, Francis Kendall, Sean Khozin, Ryan Goosen, Jianying Hu, Jason Laramie, Michael Ringel, and Nicholas Schork · 2019
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PubMedQA: A dataset for biomedical research question answering
Qiao Jin, Bhuwan Dhingra, Zhengping Liu, William Cohen, and Xinghua Lu · 2019
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Multitask learning and benchmarking with clinical time series data
Hrayr Harutyunyan, Hrant Khachatrian, David C Kale, Greg Ver Steeg, and Aram Galstyan · 2019
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Pathvqa: 30000+ questions for medical visual question answering
Xuehai He, Yichen Zhang, Luntian Mou, Eric Xing, and Pengtao Xie · 2020
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Exploring the limits of transfer learning with a unified text-to-text transformer
Colin Raffel, Noam Shazeer, Adam Roberts, Katherine Lee, Sharan Narang, Michael Matena, Yanqi Zhou, Wei Li, and Peter J. Liu · 2020
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Pegasus: pre-training with extracted gap-sentences for abstractive summarization
Jingqing Zhang, Yao Zhao, Mohammad Saleh, and Peter J. Liu · 2020
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BART: Denoising sequence-to-sequence pre-training for natural language generation, translation, and comprehension
Mike Lewis, Yinhan Liu, Naman Goyal, Marjan Ghazvininejad, Abdelrahman Mohamed, Omer Levy, Veselin Stoyanov, and Luke Zettlemoyer · 2020
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An interpretable mortality prediction model for covid-19 patients
Li Yan, Hai-Tao Zhang, Jorge Goncalves, Yang Xiao, Maolin Wang, Yuqi Guo, Chuan Sun, Xiuchuan Tang, Liang Jing, Mingyang Zhang, et al · 2020
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Adacare: Explainable clinical health status representation learning via scale-adaptive feature extraction and recalibration
Liantao Ma, Junyi Gao, Yasha Wang, Chaohe Zhang, Jiangtao Wang, Wenjie Ruan, Wen Tang, Xin Gao, and Xinyu Ma · 2020
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Concare: Personalized clinical feature embedding via capturing the healthcare context
Liantao Ma, Chaohe Zhang, Yasha Wang, Wenjie Ruan, Jiangtao Wang, Wen Tang, Xinyu Ma, Xin Gao, and Junyi Gao · 2020
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An interpretable mortality prediction model for covid-19 patients
Li Yan, Hai-Tao Zhang, Jorge Goncalves, Yang Xiao, Maolin Wang, Yuqi Guo, Chuan Sun, Xiuchuan Tang, Liang Jing, Mingyang Zhang, et al · 2020
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What disease does this patient have? a large-scale open domain question answering dataset from medical exams
Di Jin, Eileen Pan, Nassim Oufattole, Wei-Hung Weng, Hanyi Fang, and Peter Szolovits · 2021
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Paragraph-level simplification of medical texts
Ashwin Devaraj, Iain Marshall, Byron Wallace, and Junyi Jessy Li · 2021
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Advances in deep learning-based medical image analysis
Xiaoqing Liu, Kunlun Gao, Bo Liu, Chengwei Pan, Kongming Liang, Lifeng Yan, Jiechao Ma, Fujin He, Shu Zhang, Siyuan Pan, et al · 2021
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Grasp: Generic framework for health status representation learning based on incorporating knowledge from similar patients
Chaohe Zhang, Xin Gao, Liantao Ma, Yasha Wang, Jiangtao Wang, and Wen Tang · 2021
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LinkBERT: Pretraining language models with document links
Michihiro Yasunaga, Jure Leskovec, and Percy Liang · 2022
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A large language model for electronic health records
Xi Yang, Aokun Chen, Nima PourNejatian, Hoo Chang Shin, Kaleb E Smith, Christopher Parisien, Colin Compas, Cheryl Martin, Anthony B Costa, Mona G Flores, et al · 2022
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Multi-modal masked autoencoders for medical vision-and-language pre-training
Zhihong Chen, Yuhao Du, Jinpeng Hu, Yang Liu, Guanbin Li, Xiang Wan, and Tsung-Hui Chang · 2022
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A survey on in-context learning
Qingxiu Dong, Lei Li, Damai Dai, Ce Zheng, Jingyuan Ma, Rui Li, Heming Xia, Jingjing Xu, Zhiyong Wu, Tianyu Liu, et al · 2022
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Chain-of-thought prompting elicits reasoning in large language models
Jason Wei, Xuezhi Wang, Dale Schuurmans, Maarten Bosma, brian ichter, Fei Xia, Ed Chi, Quoc V Le, and Denny Zhou · 2022
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Making science simple: Corpora for the lay summarisation of scientific literature
Tomas Goldsack, Zhihao Zhang, Chenghua Lin, and Carolina Scarton · 2022
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The promise of large language models in health care
Anmol Arora and Ananya Arora · 2023
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Josh Achiam, Steven Adler, Sandhini Agarwal, Lama Ahmad, Ilge Akkaya, Florencia Leoni Aleman, Diogo Almeida, Janko Altenschmidt, Sam Altman, Shyamal Anadkat, et al · 2023
Cited alongside, same era.
The future landscape of large language models in medicine
Jan Clusmann, Fiona R Kolbinger, Hannah Sophie Muti, Zunamys I Carrero, Jan-Niklas Eckardt, Narmin Ghaffari Laleh, Chiara Maria Lavinia Löffler, Sophie-Caroline Schwarzkopf, Michaela Unger, Gregory P Veldhuizen, et al · 2023
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Foundation models for generalist medical artificial intelligence
Michael Moor, Oishi Banerjee, Zahra Shakeri Hossein Abad, Harlan M Krumholz, Jure Leskovec, Eric J Topol, and Pranav Rajpurkar · 2023
Cited alongside, same era.
Self-consistency improves chain of thought reasoning in language models
Xuezhi Wang, Jason Wei, Dale Schuurmans, Quoc V Le, Ed H. Chi, Sharan Narang, Aakanksha Chowdhery, and Denny Zhou · 2023
Cited alongside, same era.
Improving factuality and reasoning in language models through multiagent debate
Yilun Du, Shuang Li, Antonio Torralba, Joshua B Tenenbaum, and Igor Mordatch · 2023
MIMIC-IV (version 3.1), 2024
Alistair Johnson, Lucas Bulgarelli, Tom Pollard, Brian Gow, Benjamin Moody, Steven Horng, Leo Anthony Celi, and Roger Mark · 2024
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A comprehensive benchmark for covid-19 predictive modeling using electronic health records in intensive care
Junyi Gao, Yinghao Zhu, Wenqing Wang, Zixiang Wang, Guiying Dong, Wen Tang, Hao Wang, Yasha Wang, Ewen M Harrison, and Liantao Ma · 2024
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Prism: Mitigating ehr data sparsity via learning from missing feature calibrated prototype patient representations
Yinghao Zhu, Zixiang Wang, Long He, Shiyun Xie, Xiaochen Zheng, Liantao Ma, and Chengwei Pan · 2024
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Yinghao Zhu, Zixiang Wang, Junyi Gao, Yuning Tong, Jingkun An, Weibin Liao, Ewen M Harrison, Liantao Ma, and Chengwei Pan · 2024
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Mimic-iv (version 3.1), 10 2024
Alistair Johnson, Lucas Bulgarelli, Tom Pollard, Brian Gow, Benjamin Moody, Steven Horng, Leo Anthony Celi, and Mark Roger · 2024
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Cited alongside, same era.
Capabilities of gpt-4 on medical challenge problems
Harsha Nori, Nicholas King, Scott Mayer McKinney, Dean Carignan, and Eric Horvitz · 2023
Cited alongside, same era.
Large language models encode clinical knowledge
Karan Singhal, Shekoofeh Azizi, Tao Tu, S Sara Mahdavi, Jason Wei, Hyung Won Chung, Nathan Scales, Ajay Tanwani, Heather Cole-Lewis, Stephen Pfohl, et al · 2023
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Judging llm-as-a-judge with mt-bench and chatbot arena
Lianmin Zheng, Wei-Lin Chiang, Ying Sheng, Siyuan Zhuang, Zhanghao Wu, Yonghao Zhuang, Zi Lin, Zhuohan Li, Dacheng Li, Eric P. Xing, Hao Zhang, Joseph E. Gonzalez, and Ion Stoica · 2023
Cited alongside, same era.
Masked vision and language pre-training with unimodal and multimodal contrastive losses for medical visual question answering
Pengfei Li, Gang Liu, Jinlong He, Zixu Zhao, and Shenjun Zhong · 2023
Cited alongside, same era.
Llava-med: training a large language-and-vision assistant for biomedicine in one day
Chunyuan Li, Cliff Wong, Sheng Zhang, Naoto Usuyama, Haotian Liu, Jianwei Yang, Tristan Naumann, Hoifung Poon, and Jianfeng Gao · 2023
Cited alongside, same era.
Med-flamingo: a multimodal medical few-shot learner
Michael Moor, Qian Huang, Shirley Wu, Michihiro Yasunaga, Yash Dalmia, Jure Leskovec, Cyril Zakka, Eduardo Pontes Reis, and Pranav Rajpurkar · 2023
Cited alongside, same era.
Med-easi: finely annotated dataset and models for controllable simplification of medical texts
Chandrayee Basu, Rosni Vasu, Michihiro Yasunaga, and Qian Yang · 2023
Cited alongside, same era.
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Foundation models and intelligent decision-making: Progress, challenges, and perspectives
Jincai Huang, Yongjun Xu, Qi Wang, Qi Cheems Wang, Xingxing Liang, Fei Wang, Zhao Zhang, Wei Wei, Boxuan Zhang, Libo Huang, et al · 2025
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Deepseek-r1: Incentivizing reasoning capability in llms via reinforcement learning
Daya Guo, Dejian Yang, Haowei Zhang, Junxiao Song, Ruoyu Zhang, Runxin Xu, Qihao Zhu, Shirong Ma, Peiyi Wang, Xiao Bi, et al · 2025
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Toward expert-level medical question answering with large language models
Karan Singhal, Tao Tu, Juraj Gottweis, Rory Sayres, Ellery Wulczyn, Mohamed Amin, Le Hou, Kevin Clark, Stephen R Pfohl, Heather Cole-Lewis, et al · 2025
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Benchmark evaluation of deepseek large language models in clinical decision-making
Sarah Sandmann, Stefan Hegselmann, Michael Fujarski, Lucas Bickmann, Benjamin Wild, Roland Eils, and Julian Varghese · 2025
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Xagent: An autonomous agent for complex task solving
XAgent Team · 2025
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Multi-agent collaboration mechanisms: A survey of llms
Khanh-Tung Tran, Dung Dao, Minh-Duong Nguyen, Quoc-Viet Pham, Barry O’Sullivan, and Hoang D Nguyen · 2025
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Holistic evaluation of large language models for medical applications
Nigam Shah, Mike Pfeffer, and Percy Liang · 2025
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Medagentsbench: Benchmarking thinking models and agent frameworks for complex medical reasoning
Xiangru Tang, Daniel Shao, Jiwoong Sohn, Jiapeng Chen, Jiayi Zhang, Jinyu Xiang, Fang Wu, Yilun Zhao, Chenglin Wu, Wenqi Shi, et al · 2025
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Why do multi-agent llm systems fail?
Mert Cemri, Melissa Z Pan, Shuyi Yang, Lakshya A Agrawal, Bhavya Chopra, Rishabh Tiwari, Kurt Keutzer, Aditya Parameswaran, Dan Klein, Kannan Ramchandran, et al · 2025
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If multi-agent debate is the answer, what is the question?
Hangfan Zhang, Zhiyao Cui, Xinrun Wang, Qiaosheng Zhang, Zhen Wang, Dinghao Wu, and Shuyue Hu · 2025
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Autogpt: An autonomous gpt-4 experiment
Significant Gravitas · 2025
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Colacare: Enhancing electronic health record modeling through large language model-driven multi-agent collaboration
Zixiang Wang, Yinghao Zhu, Huiya Zhao, Xiaochen Zheng, Dehao Sui, Tianlong Wang, Wen Tang, Yasha Wang, Ewen Harrison, Chengwei Pan, Junyi Gao, and Liantao Ma · 2025
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It’s time to bench the medical exam benchmark
Inioluwa Deborah Raji, Roxana Daneshjou, and Emily Alsentzer · 2025
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Towards understanding llm-generated biomedical lay summaries
Rohan Charudatt Salvi, Swapnil Panigrahi, Dhruv Jain, Shweta Yadav, and Md Shad Akhtar · 2025
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Collaborative document simplification using multi-agent systems
Dengzhao Fang, Jipeng Qiang, Xiaoye Ouyang, Yi Zhu, Yunhao Yuan, and Yun Li · 2025
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In-hospital mortality prediction among intensive care unit patients with acute ischemic stroke: A machine learning approach
Jack A Cummins, Ben S Gerber, Mayuko Ito Fukunaga, Nils Henninger, Catarina I Kiefe, and Feifan Liu · 2025
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Learnable prompt as pseudo-imputation: Rethinking the necessity of traditional ehr data imputation in downstream clinical prediction
Weibin Liao, Yinghao Zhu, Zhongji Zhang, Yuhang Wang, Zixiang Wang, Xu Chu, Yasha Wang, and Liantao Ma · 2025
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Exploring the relationship between dietary intake and clinical outcomes in peritoneal dialysis patients stratified by serum albumin levels: A 12-year follow-up using fine-grained electronic medical records data
Yueying Wu, Junyi Gao, Wen Tang, Chunyan Su, Yinghao Zhu, Tianlong Wang, Ling Wang, Weibin Liao, Xu Chu, Yasha Wang, et al · 2025
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Gemini 2.5: Our most intelligent ai model
Google Deepmind · 2025
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‘smolagents‘: a smol library to build great agentic systems
Aymeric Roucher, Albert Villanova del Moral, Thomas Wolf, Leandro von Werra, and Erik Kaunismäki · 2025
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Openmanus: An open-source framework for building general ai agents, 2025
Xinbin Liang, Jinyu Xiang, Zhaoyang Yu, Jiayi Zhang, Sirui Hong, Sheng Fan, and Xiao Tang · 2025
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Owl: Optimized workforce learning for general multi-agent assistance in real-world task automation, 2025
Mengkang Hu, Yuhang Zhou, Wendong Fan, Yuzhou Nie, Bowei Xia, Tao Sun, Ziyu Ye, Zhaoxuan Jin, Yingru Li, Zeyu Zhang, Yifeng Wang, Qianshuo Ye, Ping Luo, and Guohao Li · 2025
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Shuai Bai, Keqin Chen, Xuejing Liu, Jialin Wang, Wenbin Ge, Sibo Song, Kai Dang, Peng Wang, Shijie Wang, Jun Tang, et al · 2025
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