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Clinical decision making (CDM) is a complex, dynamic process crucial to healthcare delivery, yet it remains a significant challenge for artificial intelligence systems.
An overview of the uses of standardized patients for teaching and evaluating clinical skills. aamc
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Bleu: a method for automatic evaluation of machine translation
Kishore Papineni, Salim Roukos, Todd Ward, and Wei-Jing Zhu · 2002
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Medical exam question answering with large-scale reading comprehension
Xiao Zhang, Ji Wu, Zhiyang He, Xien Liu, and Ying Su · 2018
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Pubmedqa: A dataset for biomedical research question answering
Qiao Jin, Bhuwan Dhingra, Zhengping Liu, William W Cohen, and Xinghua Lu · 2019
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Bertscore: Evaluating text generation with bert
Tianyi Zhang, Varsha Kishore, Felix Wu, Kilian Q Weinberger, and Yoav Artzi · 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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Retrieval-augmented generation for knowledge-intensive nlp tasks
Patrick Lewis, Ethan Perez, Aleksandra Piktus, Fabio Petroni, Vladimir Karpukhin, Naman Goyal, Heinrich Küttler, Mike Lewis, Wen-tau Yih, Tim Rocktäschel, et al · 2020
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" the human body is a black box" supporting clinical decision-making with deep learning
Mark Sendak, Madeleine Clare Elish, Michael Gao, Joseph Futoma, William Ratliff, Marshall Nichols, Armando Bedoya, Suresh Balu, and Cara O’Brien · 2020
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An overview of clinical decision support systems: benefits, risks, and strategies for success
Reed T Sutton, David Pincock, Daniel C Baumgart, Daniel C Sadowski, Richard N Fedorak, and Karen I Kroeker · 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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Multi-agent deep reinforcement learning: a survey
Sven Gronauer and Klaus Diepold · 2022
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Medmcqa: A large-scale multi-subject multi-choice dataset for medical domain question answering
Ankit Pal, Logesh Kumar Umapathi, and Malaikannan Sankarasubbu · 2022
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Self-consistency improves chain of thought reasoning in language models
Xuezhi Wang, Jason Wei, Dale Schuurmans, Quoc Le, Ed Chi, Sharan Narang, Aakanksha Chowdhery, and Denny Zhou · 2022
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Chain-of-thought prompting elicits reasoning in large language models
Jason Wei, Xuezhi Wang, Dale Schuurmans, Maarten Bosma, Fei Xia, Ed Chi, Quoc V Le, Denny Zhou, et al · 2022
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Internvl: Scaling up vision foundation models and aligning for generic visual-linguistic tasks
Zhe Chen, Jiannan Wu, Wenhai Wang, Weijie Su, Guo Chen, Sen Xing, Muyan Zhong, Qinglong Zhang, Xizhou Zhu, Lewei Lu, Bin Li, Ping Luo, Tong Lu, Yu Qiao, and Jifeng Dai · 2023
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Lmdeploy: A toolkit for compressing, deploying, and serving llm
LMDeploy Contributors · 2023
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Use of gpt-4 to diagnose complex clinical cases, 2023
Alexander V Eriksen, Sören Möller, and Jesper Ryg · 2023
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How does chatgpt perform on the united states medical licensing examination (usmle)? the implications of large language models for medical education and knowledge assessment
Aidan Gilson, Conrad W Safranek, Thomas Huang, Vimig Socrates, Ling Chi, Richard Andrew Taylor, David Chartash, et al · 2023
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Don’t generate, discriminate: A proposal for grounding language models to real-world environments
Yu Gu, Xiang Deng, and Yu Su · 2023
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Leveraging pre-trained large language models to construct and utilize world models for model-based task planning
Lin Guan, Karthik Valmeekam, Sarath Sreedharan, and Subbarao Kambhampati · 2023
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Dynamic llm-agent network: An llm-agent collaboration framework with agent team optimization
Zijun Liu, Yanzhe Zhang, Peng Li, Yang Liu, and Diyi Yang · 2023
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Gpt-4v(ision) system card
OpenAI · 2023
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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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Medagents: Large language models as collaborators for zero-shot medical reasoning
Xiangru Tang, Anni Zou, Zhuosheng Zhang, Yilun Zhao, Xingyao Zhang, Arman Cohan, and Mark Gerstein · 2023
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Gemini: a family of highly capable multimodal models
Gemini Team, Rohan Anil, Sebastian Borgeaud, Yonghui Wu, Jean-Baptiste Alayrac, Jiahui Yu, Radu Soricut, Johan Schalkwyk, Andrew M Dai, Anja Hauth, et al · 2023
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Cmb: A comprehensive medical benchmark in chinese
Xidong Wang, Guiming Hardy Chen, Dingjie Song, Zhiyi Zhang, Zhihong Chen, Qingying Xiao, Feng Jiang, Jianquan Li, Xiang Wan, Benyou Wang, et al · 2023
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Autogen: Enabling next-gen llm applications via multi-agent conversation framework
Qingyun Wu, Gagan Bansal, Jieyu Zhang, Yiran Wu, Shaokun Zhang, Erkang Zhu, Beibin Li, Li Jiang, Xiaoyun Zhang, and Chi Wang · 2023
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Huatuogpt, towards taming language model to be a doctor
Hongbo Zhang, Junying Chen, Feng Jiang, Fei Yu, Zhihong Chen, Jianquan Li, Guiming Chen, Xiangbo Wu, Zhiyi Zhang, Qingying Xiao, et al · 2023
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Medagents: Large language models as collaborators for zero-shot medical reasoning, 2024
Xiangru Tang, Anni Zou, Zhuosheng Zhang, Ziming Li, Yilun Zhao, Xingyao Zhang, Arman Cohan, and Mark Gerstein · 2024
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Gemma 2: Improving open language models at a practical size
Gemma Team, Morgane Riviere, Shreya Pathak, Pier Giuseppe Sessa, Cassidy Hardin, Surya Bhupatiraju, Léonard Hussenot, Thomas Mesnard, Bobak Shahriari, Alexandre Ramé, et al · 2024
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Towards generalist biomedical ai
Tao Tu, Shekoofeh Azizi, Danny Driess, Mike Schaekermann, Mohamed Amin, Pi-Chuan Chang, Andrew Carroll, Charles Lau, Ryutaro Tanno, Ira Ktena, et al · 2024
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Qwen2-vl: Enhancing vision-language model’s perception of the world at any resolution
Peng Wang, Shuai Bai, Sinan Tan, Shijie Wang, Zhihao Fan, Jinze Bai, Keqin Chen, Xuejing Liu, Jialin Wang, Wenbin Ge, et al · 2024
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Asclepius: A spectrum evaluation benchmark for medical multi-modal large language models
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Medbench: A large-scale chinese benchmark for evaluating medical large language models
Yan Cai, Linlin Wang, Ye Wang, Gerard de Melo, Ya Zhang, Yanfeng Wang, and Liang He · 2024
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Benchmarking large language models on answering and explaining challenging medical questions
Hanjie Chen, Zhouxiang Fang, Yash Singla, and Mark Dredze · 2024
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Cod, towards an interpretable medical agent using chain of diagnosis
Junying Chen, Chi Gui, Anningzhe Gao, Ke Ji, Xidong Wang, Xiang Wan, and Benyou Wang · 2024
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Gmai-mmbench: A comprehensive multimodal evaluation benchmark towards general medical ai
Pengcheng Chen, Jin Ye, Guoan Wang, Yanjun Li, Zhongying Deng, Wei Li, Tianbin Li, Haodong Duan, Ziyan Huang, Yanzhou Su, et al · 2024
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Zhihao Fan, Jialong Tang, Wei Chen, Siyuan Wang, Zhongyu Wei, Jun Xi, Fei Huang, and Jingren Zhou · 2024
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Retrieval-augmented generation for large language models: A survey, 2024
Yunfan Gao, Yun Xiong, Xinyu Gao, Kangxiang Jia, Jinliu Pan, Yuxi Bi, Yi Dai, Jiawei Sun, Meng Wang, and Haofen Wang · 2024
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A survey on retrieval-augmented text generation for large language models, 2024
Yizheng Huang and Jimmy Huang · 2024
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Adaptive collaboration strategy for llms in medical decision making
Yubin Kim, Chanwoo Park, Hyewon Jeong, Yik Siu Chan, Xuhai Xu, Daniel McDuff, Cynthia Breazeal, and Hae Won Park · 2024
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Wenxuan Wang, Yihang Su, Jingyuan Huan, Jie Liu, Wenting Chen, Yudi Zhang, Cheng-Yi Li, Kao-Jung Chang, Xiaohan Xin, Linlin Shen, et al · 2024
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Officebench: Benchmarking language agents across multiple applications for office automation
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Medical graph rag: Towards safe medical large language model via graph retrieval-augmented generation, 2024
Junde Wu, Jiayuan Zhu, and Yunli Qi · 2024
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Doclens: Multi-aspect fine-grained medical text evaluation
Yiqing Xie, Sheng Zhang, Hao Cheng, Pengfei Liu, Zelalem Gero, Cliff Wong, Tristan Naumann, Hoifung Poon, and Carolyn Rose · 2024
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Benchmarking retrieval-augmented generation for medicine, 2024
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Clinicalagent: Clinical trial multi-agent system with large language model-based reasoning, 2024
Ling Yue, Sixue Xing, Jintai Chen, and Tianfan Fu · 2024
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Almanac copilot: Towards autonomous electronic health record navigation
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Eagle: Expert-guided self-enhancement for preference alignment in pathology large vision-language model
Meidan Ding, Jipeng Zhang, Wenxuan Wang, Haiqin Zhong, Xiaoqin Wang, Xinheng Lyu, Wenting Chen, and Linlin Shen · 2025
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Baichuan-m2: Scaling medical capability with large verifier system
Chengfeng Dou, Chong Liu, Fan Yang, Fei Li, Jiyuan Jia, Mingyang Chen, Qiang Ju, Shuai Wang, Shunya Dang, Tianpeng Li, et al · 2025
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Towards a holistic framework for multimodal llm in 3d brain ct radiology report generation
Cheng-Yi Li, Kao-Jung Chang, Cheng-Fu Yang, Hsin-Yu Wu, Wenting Chen, Hritik Bansal, Ling Chen, Yi-Ping Yang, Yu-Chun Chen, Shih-Pin Chen, et al · 2025
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Asclepius: A spectrum evaluation benchmark for medical multi-modal large language models
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A comprehensive evaluation of multi-modal large language models for endoscopy analysis
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WSI-Agents: A Collaborative Multi-Agent System for Multi-Modal Whole Slide Image Analysis
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Beyond the leaderboard: Rethinking medical benchmarks for large language models
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A survey of LLM-based agents in medicine: How far are we from baymax?
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Towards evaluating and building versatile large language models for medicine
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Medreason: Eliciting factual medical reasoning steps in llms via knowledge graphs
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