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We present the design process and findings of the pre-conference workshop at the Machine Learning for Healthcare Conference (2024) entitled Red Teaming Large Language Models for Healthcare, which took place on August 15, 2024.
Flaws in clinical reasoning: a common cause of diagnostic error
Caroline Wellbery · 2011
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Debadutta Dash, Rahul Thapa, Juan M. Banda, Akshay Swaminathan, Morgan Cheatham, Mehr Kashyap, Nikesh Kotecha, Jonathan H. Chen, Saurabh Gombar, Lance Downing, Rachel Pedreira, Ethan Goh, Angel Arnaout, Garret Kenn Morris, Honor Magon, Matthew P Lungren, Eric Horvitz, and Nigam H. Shah · 2023
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Walking a tightrope – evaluating large language models in high-risk domains
Chia-Chien Hung, Wiem Ben Rim, Lindsay Frost, Lars Bruckner, and Carolin Lawrence · 2023
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Clinical camel: An open-source expert-level medical language model with dialogue-based knowledge encoding
Augustin Toma, Patrick R Lawler, Jimmy Ba, Rahul G Krishnan, Barry B Rubin, and Bo Wang · 2023
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A framework to assess clinical safety and hallucination rates of LLMs for medical text summarisation
Elham Asgari, Nina Montaña-Brown, Magda Dubois, Saleh Khalil, Jasmine Balloch, and Dominic Pimenta · 2024
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Red-teaming for generative ai: Silver bullet or security theater?
Michael Feffer, Anusha Sinha, Wesley H Deng, Zachary C Lipton, and Hoda Heidari · 2024
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Evaluation and mitigation of the limitations of large language models in clinical decision-making
Paul Hager, Friederike Jungmann, Robbie Holland, Kunal Bhagat, Inga Hubrecht, Manuel Knauer, Jakob Vielhauer, Marcus Makowski, Rickmer Braren, Georgios Kaissis, and Daniel Rueckert · 2024
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ChatGPT in healthcare: A taxonomy and systematic review
Jianning Li, Amin Dada, Behrus Puladi, Jens Kleesiek, and Jan Egger · 2024
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Beyond accuracy: Investigating error types in GPT-4 responses to USMLE questions
Soumyadeep Roy, Aparup Khatua, Fatemeh Ghoochani, Uwe Hadler, Wolfgang Nejdl, and Niloy Ganguly · 2024
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Lessons from red teaming 100 generative ai products
Blake Bullwinkel, Amanda J. Minnich, Shiven Chawla, Gary Lopez, Martin Pouliot, Whitney Maxwell, Joris de Gruyter, Katherine Pratt, Saphir Qi, Nina Chikanov, Roman Lutz, Raja Sekhar Rao Dheekonda, Bolor-Erdene Jagdagdorj, Eugenia Kim, Justin Song, Keegan Hines, Daniel Jones, Giorgio Severi, Richard Lundeen, Sam Vaughan, Victoria Westerhoff, Pete Bryan, Ram Shankar Siva Kumar, Yonatan Zunger, Chang Kawaguchi, and Mark Russinovich · 2025
Red teaming ChatGPT in medicine to yield real-world insights on model behavior
Crystal T Chang, Hodan Farah, Haiwen Gui, Shawheen Justin Rezaei, Charbel Bou-Khalil, Ye-Jean Park, Akshay Swaminathan, Jesutofunmi A Omiye, Akaash Kolluri, Akash Chaurasia, et al · 2025
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Evaluating large language models and agents in healthcare: key challenges in clinical applications
Xiaolan Chen, Jiayang Xiang, Shanfu Lu, Yexin Liu, Mingguang He, and Danli Shi · 2025
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A survey on hallucination in large language models: Principles, taxonomy, challenges, and open questions, January 2025
Lei Huang, Weijiang Yu, Weitao Ma, Weihong Zhong, Zhangyin Feng, Haotian Wang, Qianglong Chen, Weihua Peng, Xiaocheng Feng, Bing Qin, and Ting Liu · 2025
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Against the Achilles’ heel: A survey on red teaming for generative models
Lizhi Lin, Honglin Mu, Zenan Zhai, Minghan Wang, Yuxia Wang, Renxi Wang, Junjie Gao, Yixuan Zhang, Wanxiang Che, Timothy Baldwin, Xudong Han, and Haonan Li · 2025
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Evaluating the use of large language models to provide clinical recommendations in the emergency department
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Christopher Y K Williams, Brenda Y Miao, Aaron E Kornblith, and Atul J Butte · 2041
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