Accès ouvert déclaré 2025 conference-paper

NTCIR-18 MedNLP-CHAT Determining Medical, Ethical and Lega Risks in Patient-Doctor Conversations: Task Overview

Eiji Aramaki, Shoko Wakamiya, Shuntaro Yada, Shohei Hisada, Tomohiro Nishiyama, Lenard Paulo Tamayo, Jingnan Xiao, Axalia Levenchaud, Pierre Zweigenbaum, Christoph Otto, Jerycho Pasniczek, Philippe Thomas, Nathan Pohl, Wiebke Duettmann, Lisa Raithel, Roland Roller

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This paper presents an overview of the Medical Natural Language Processing for AI Chat (MedNLP-CHAT) task, conducted as part of the shared task at NTCIR-18. Recently, medical chatbot services have emerged as a promising solution to address the shortage of medical and healthcare professionals. However, the potential risks associated with these chatbots remain insufficiently understood. Given this context, we designed the MedNLP-CHAT task to evaluate medical chatbots from multiple risk perspectives, including medical, legal, and ethical aspects. In this shared task, participants were required to analyze a given medical question along with the corresponding chatbot response and determine whether the response posed a potential medical, legal, or ethical risk (binary classification). Nine teams participated in this task applying different approaches, yielding valuable insights.

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