El 5 de junio de 2024, el prof. Dr. Yavuz Kiyak, de la Gazi University Faculty of Medicine (Turquía) impartió un webinar sobre el uso de la inteligencia artificial para generar casos, preguntas de respuesta múltiple y tests de concordancia script.
Transcripción (hecha por ZOOM AI):
| Yavuz proceeded to give a briefing on AI and demonstrated how to use chatbots, explaining the terminology and the importance of open-source models. He team also discussed various large language models, including Chat GPT, GPT-3, and Llama. | |
| AI Models for Medical Training | |
| Yavuz presented the potential of using AI models like Chat GPT for generating medical case vignettes and multiple-choice questions. He mentioned a recent study showing comparable results with Chat GPT to human-generated cases, indicating its potential as a tool for medical student training. Yavuz also discussed the continuous advancements in AI, such as the release of GPT-4 and GPT-4 Omniverse, and highlighted the growing use of AI in generating medical case vignettes and images. | |
| Developing Effective Prompts for Medical Education | |
| Yavuz discussed the challenges of generating clinical vignettes and multiple-choice questions for medical education using simple prompts. He stressed the importance of high-quality prompts to avoid superficial and unhelpful outputs. Yavuz shared his experience in developing an effective prompt for generating multiple-choice questions, which was published in the Journal of Medical Education. He also mentioned an ongoing study in Turkey where ChatGPT-generated questions were incorporated into an exam, demonstrating their effectiveness in differentiating between high and low performing students. However, he pointed out a problem with question number 3, highlighting that several response options were deemed nonfunctional. | |
| Large Language Models for Question Generation | |
| Yavuz discussed the capabilities of large language models, specifically ChatGPT, in generating useful multiple-choice questions (MCQs) and concordance test items (CTIs). He highlighted the importance of designing appropriate prompts to generate high-quality questions and CTIs. Yavuz also introduced a new, detailed prompt for generating CTIs, which he demonstrated by creating an example question. He emphasized the potential benefits of these tools for medical education, but also cautioned about the possibility of inaccurate information provided by these language models. | |
| Reviewing Large Language Models and Tools | |
| Yavuz, the host of a monthly medical education YouTube channel and a daily Twitter account, highlighted the need for reviewing the outputs of large language models due to their potential for inaccurate knowledge. The discussion also covered topics such as the validation of eassions, the role of Om Aspex in clinical case validation, and the development of prompts for specific purposes in hypothesis generation. Joaquín thanked everyone for their contributions and introduced new tools including the Mcq. Test generator and the script Concordance test generator. | |
| Concordance Test Usage and GPT-4 Tool | |
| Joaquín and Yavuz discussed the underuse of the Concordance test in Spain and the potential benefits of using a question generation tool based on the latest GPT-4 model. Yavuz demonstrated the tool's capabilities, and Joaquín expressed interest in its potential as a learning aid for students, but highlighted the need for further trials. There was also mention of participants from various locations, including Poland and Turkey, and the possibility of Javuz presenting some examples. | |
| Diversified Discussions and Unresolved Issues | |
| The team engaged in a broad range of discussions, including technical issues, potential scheduling changes, and voting procedures. They addressed a problem with system connectivity, an application process, and an issue with Eden scholarships. Additionally, there were discussions about the impact of artificial intelligence, a stalled survey, and personal matters. |
