Familiarity to Application and Attitude (An Exploratory Study)

Large Language Models (LLMs) are transformative technologies with the potential to significantly impact specialized fields, including medical engineering. It is important to understand user attitudes and behaviors to guide the effective integration of LLMS in medical engineering. Objective: This study aimed to map the familiarity, usage patterns, attitudes, and perceived concerns regarding LLMs among ۳۸ respondents, the majority were undergraduate and graduate students. Methods: A cross-sectional online survey was conducted through an Instagram page dedicated to medical engineering, which had approximately ۱۴,۸۰۰ followers. Of ۹۸ visitors to the survey, ۳۸ completed the questionnaire, resulting in a response rate of ۳۸.۷%. Data were analyzed using descriptive statistics. Results: Most respondents were undergraduate students (۷۵%) and graduate students (۲۲%). ۶۷% reported prior use of LLMS, and ۷۲% used them daily or several times a week. The most common reported use was for learning specialized concepts (۲۴%). Regarding attitudes, ۷۸% of respondents agreed that LLMs increase productivity. Additionally, ۸۸% highlighted their supportive role in research. However, a major concern was identified regarding the "scientific accuracy of outputs" (۷۲% agreed). Furthermore, ۹۵% of participants indicated their intention to use LLMS more frequently in the future. Conclusion: The findings indicate that LLMs are widely accepted and viewed positively as assistive tools among Iran's medical engineering students and professionals. However, concerns about output validity highlight the need for educational guidelines on critical use and suggest the potential benefit of developing domain-specific LLMs.

کلیدواژه ها:

Large Language Models ، Generative Artificial Intelligence ، ChatGPT ، Medical Engineering ، Biomedical Engineering ، Survey ، Attitude ، Technology Acceptance ، Iran