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This paper is in the following e-collection/theme issue:

Chatbots and Conversational Agents (802) Emerging Technologies for Rehabilitation (394) Postoperative Rehabilitation (76) Perioperative Patient Education (31) Generative Language Models Including ChatGPT (865) Responsible Health AI (100)

Published on in Vol 27 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/73717, first published .
Exploring Patient Perspectives, Engagement, and Output Quality in Doctor-Supervised Use of Artificial Intelligence During Informed Consent Consultation With ChatGPT and Retrieval Augmented Generation (RAG): Quantitative Exploratory Study

Exploring Patient Perspectives, Engagement, and Output Quality in Doctor-Supervised Use of Artificial Intelligence During Informed Consent Consultation With ChatGPT and Retrieval Augmented Generation (RAG): Quantitative Exploratory Study

Exploring Patient Perspectives, Engagement, and Output Quality in Doctor-Supervised Use of Artificial Intelligence During Informed Consent Consultation With ChatGPT and Retrieval Augmented Generation (RAG): Quantitative Exploratory Study

Authors of this article:

Sascha Donner1 Author Orcid Image ;   Poroshista Knauer2 Author Orcid Image ;   Arne Kienzle2 Author Orcid Image ;   Jesse Dinneen3 Author Orcid Image ;   Joost Burger2 Author Orcid Image ;   Carsten Perka2 Author Orcid Image ;   Stefanie Donner2 Author Orcid Image
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Conference Proceedings

  1. Hou Q, Liu G, Zhu P. Proceedings of the 2025 4th International Conference on Artificial Intelligence and Education. HMA: A Hierarchical Multi-Agent System for Document Question Answering View