Education Research: Bridging the Artificial Intelligence Training Gap

Abstract

Background and Objectives: As artificial intelligence (AI) rapidly becomes an integral tool in clinical neurology, future clinicians will need to master its application in patient care. While previous studies focused primarily on medical students' perspectives, our survey, addressed to Italian neurology residents, aims to assess their familiarity with AI tools and identify educational needs of learners close to clinical practice and care delivery. Methods: A cross-sectional, web-based survey designed by the University of Milan was distributed nationwide to neurology residents from May 22 through July 30, 2025. The questionnaire included items on demographics, self-assessed AI knowledge, exposure to AI training, clinical applications, perceived challenges, and attitudes toward the impact of AI on neurology practice. Descriptive statistics and association analyses were performed. Results: < 0.001), while nearly all respondents expressed interest in further AI training (93.1%). The most familiar application was generative AI for clinical decision support (64.2%), and neuroimaging was rated as the first AI integration area (mean priority 2.99). Main barriers to AI application included concerns about reliability (71.1%) and data privacy (43.9%). Regarding career perspectives, 41.6% of residents believed that AI will create new job opportunities, whereas most (89%) agreed that the AI revolution will not replace human professionals. Discussion: Despite the limited number of participants, our survey provides a representative snapshot of AI knowledge, use, and attitudes among neurology residents in Italy, a critical country in the digital health care transformation, contributing important evidence for international shared recommendations on AI educational needs to support future clinical practice. Although AI tools are widely used, most residents had only basic knowledge and limited formal training, prompting calls for more structured, learner-centered educational modules to be integrated into neurology curricula.

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