Hopson Spencer, Mildon Carson, Hassard Kyle, Kubalek Corbyn, Laverty Lauren, Urie Paul, Corte Dennis Della
Department of Physics and Astronomy, Brigham Young University, Provo, UT, USA.
BMC Med Educ. 2025 Jul 3;25(1):999. doi: 10.1186/s12909-025-07556-2.
The integration of artificial intelligence (AI) into healthcare is rapidly advancing, with profound implications for medical practice. However, a gap exists in formal AI education for pre-medical students. This study evaluates the effectiveness of the AI in Medicine Association (AIM), an extracurricular program designed to equip pre-medical students with foundational AI knowledge.
A quasi-experimental pretest-posttest control group design was employed, comparing knowledge acquisition between students participating in the AIM program (cohort group) and a control group of students not participating. The intervention spanned four weeks and included hands-on AI training, ethical considerations, data preprocessing, and model evaluation. Pretest and posttest assessments measured AI knowledge and pathology-related skills.
Participants in the AIM program demonstrated significant improvements in both AI knowledge and pathology-related scores. The cohort group showed a large effect size across all measured domains, particularly in pathology, with Cohen's d values ranging from 1.83 to 4.74. Statistical analysis confirmed robust, significant improvements in test scores (t-test and Mann-Whitney U test, p < 0.001). There was no significant correlation between previous AI experience or attitudes toward AI and overall score improvement.
The AIM program effectively improved pre-medical students' understanding of AI and its application in medicine, particularly in pathology. This study highlights the potential of extracurricular programs to address the need for AI education in medical curricula, especially in the pre-medical phase, and suggests that such initiatives could serve as a model for other institutions seeking to integrate AI education into healthcare training.
人工智能（AI）在医疗保健领域的整合正在迅速推进，对医疗实践具有深远影响。然而，医学预科学生的正规人工智能教育存在差距。本研究评估了医学人工智能协会（AIM）这一课外项目的有效性，该项目旨在为医学预科学生提供人工智能基础知识。
采用准实验性前测-后测对照组设计，比较参与AIM项目的学生（队列组）和未参与的对照组学生之间的知识获取情况。干预为期四周，包括人工智能实践培训、伦理考量、数据预处理和模型评估。前测和后测评估测量了人工智能知识和病理学相关技能。
AIM项目的参与者在人工智能知识和病理学相关分数方面均有显著提高。队列组在所有测量领域均显示出较大的效应量，尤其是在病理学方面，科恩d值范围为1.83至4.74。统计分析证实测试分数有稳健、显著的提高（t检验和曼-惠特尼U检验，p < 0.001）。先前的人工智能经验或对人工智能的态度与总体分数提高之间没有显著相关性。
AIM项目有效地提高了医学预科学生对人工智能及其在医学中的应用的理解，尤其是在病理学方面。本研究强调了课外项目满足医学课程中人工智能教育需求的潜力，特别是在医学预科阶段，并表明此类举措可为其他寻求将人工智能教育纳入医疗培训的机构提供范例。
