METHODS: A cross-sectional study was conducted among 325 medical students in Kerala using a pre-validated, semi structured questionnaire. The survey collected demographic data, any past educational experience about AI, participants\' self-evaluation of their knowledge and evaluated self-perceived understanding of applications of AI in medicine. Participants responded to twelve Likert-scale questions targeting perceptions and ethical aspects and their opinions on suggested topics on AI to be included in their curriculum.
CONCLUSIONS: AI was viewed as an assistive technology for reducing medical errors by 57.2% students and 54.2% believed AI could enhance medical decision accuracy. About 49% agreed that AI could potentially improve accessibility to healthcare. Concerns about AI replacing physicians were reported by 37.6% and 69.2% feared a reduction in the humanistic aspect of medicine. Students were worried about challenges to trust (52.9%), patient-physician relationships (54.5%) and breach of professional confidentiality (53.5%). Only 3.7% felttotally competent in informing patients about features and risks associated with AI applications. Strong demand for structured AI training was expressed, particularly on reducing medical errors (76.9%) and ethical issues (79.4%).
CONCLUSIONS: This study highlights medical students\' demand for structured AI training in undergraduate curricula, emphasising its importance in addressing evolving healthcare needs and ethical considerations. Despite widespread ethical concerns, the majority perceive AI as an assistive technology in healthcare. These findings provide valuable insights for curriculum development and defining learning outcomes in AI education for medical students.
方法:在喀拉拉邦的325名医学生中进行了一项横断面研究,半结构化问卷。调查收集了人口统计数据,任何过去关于人工智能的教育经验,参与者对他们的知识进行自我评估,并评估他们对人工智能在医学中应用的自我感知理解。参与者回答了十二个李克特量表的问题,这些问题针对的是观念和道德方面,以及他们对课程中所建议的AI主题的意见。
结论:AI被视为一种辅助技术,用于减少57.2%的学生和54.2%的学生的医疗错误,认为AI可以提高医疗决策的准确性。大约49%的人认为人工智能可能会改善医疗保健的可及性。37.6%的人担心人工智能取代医生,69.2%的人担心医学的人文方面会减少。学生担心信任的挑战(52.9%),医患关系(54.5%)和违反专业保密(53.5%).只有3.7%的人完全有能力告知患者与AI应用相关的特征和风险。表达了对结构化AI培训的强烈需求,特别是在减少医疗差错(76.9%)和道德问题(79.4%)方面。
结论:这项研究强调了医学生对本科课程中结构化AI培训的需求,强调其在解决不断变化的医疗保健需求和道德考虑方面的重要性。尽管存在广泛的伦理问题,大多数人认为人工智能是医疗保健中的辅助技术。这些发现为课程开发和定义医学生AI教育中的学习成果提供了有价值的见解。