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Updated: May 15, 2026

Manufacture of a Multi-Purpose Low-Cost Animal Bench-Model for Teaching Tracheostomy
Published on: May 18, 2019
Evaluating the quality of expert-trained generative artificial intelligence when answering tracheostomy-related
B Gorst1, E Johnstone2,3, J Abbas4
1School of Biological Sciences, Faculty of Biology, Medicine and Health University of Manchester Manchester UK.
Abstract:
Tracheostomy training is effective, yet significant face-to-face training barriers remain. We aimed to develop, train and test a generative artificial intelligence instructor (AI-Brendan). AI-Brendan utilises the base model of ChatGPT-4.0, augmented by a curated dataset of expert-answered tracheostomy care questions, delivered with a contextually responsive conversational interface (Inworld). AI-Brendan's responses to five randomly selected questions were compared with ChatGPT-4.0 and five human expert responses using a modified Ensuring Quality Information for Patients tool, rated by six blinded independent adjudicators. A total of 450 Ensuring Quality Information for Patients scores were generated from responses (150 each from AI-Brendan, ChatGPT-4.0 and Experts), with no alarming responses. AI-Brendan (mean score 12.6 ± 3.0) performed significantly better than ChatGPT-4.0 (11.4 ± 2.4) and Experts (8.9 ± 3.6, ANOVA p < 0.01). Friedman testing demonstrated no significant differences across repeated responses, indicating consistency. Within-question variability indicated highly consistent responses. Inter-rater reliability was good (Cronbach's α = 0.863). Adjudicator's ability to correctly determine answer source was 50% for Experts, 39% for AI-Brendan and 33% for ChatGPT-4.0. Our expert-trained generative artificial intelligence produced "better" answers than open-source ChatGPT-4.0 and experts when rated by the modified Ensuring Quality Information for Patients tool. A validated artificial intelligence instructor has significant implications for addressing training barriers, increasing efficacy, overcoming scheduling, financial or geographical limitations, offering consistent, accessible and flexible training.
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