人工智能赋能医学免疫学：从前沿研究到教育创新
Artificial Intelligence Empowering Medical Immunology: From Cutting-Edge Research to Educational Innovation
DOI: 10.12677/ve.2026.151043, PDF,    科研立项经费支持
作者: 马兴铭：西华大学大健康管理学院，四川 成都
关键词: 人工智能；医学免疫学；医学教育；教育创新；科学研究；Artificial Intelligence； Medical Immunology； Medical Education； Education Innovation； Scientific Research
摘要: 人工智能技术已成为科技与产业变革的关键驱动力，正在迅速赋能医疗健康服务和医学教育。本文总结了人工智能在医学免疫学从前沿研究到教育创新的赋能作用。人工智能已经革命性地改变了多个免疫生物医学领域，在疾病标志物鉴别与诊断、个性化治疗策略制定、药物筛选与研发、候选疫苗开发等免疫学领域取得显著进展，并将研究成果的内容转化为医学免疫学教学资源。人工智能通过构建沉浸式虚拟学习环境、提供个性化自适应学习路径、实施智能评估与实时反馈等方式，改变了传统医学免疫学的教学模式，显著提升了学生的学习兴趣和参与度，更拓展了其学术视野，培养了创新思维和学术研究能力。然而，人工智能赋能医学免疫学教育教学面临学科与人工智能融合不足、技术难题待解、实施成本高昂、数据安全与隐私保护、算法偏见、AI幻觉等诸多挑战，未来通过突破关键技术、完善数据治理体系等措施，推动人工智能赋能医学免疫学的研究与教育创新。
Abstract: Artificial intelligence (AI) technology is a key driver of technological and industrial transformation, rapidly empowering healthcare services and medical education. This article summarized the empowering role of AI in medical immunology, which spanned from cutting-edge research to educational innovation. AI had revolutionized multiple areas of immune-biomedicine, which achieved a significant progress in immunology areas such as disease biomarker identification and diagnosis, personalized treatment strategy development, drug screening and development, and candidate vaccine development. Research findings were being transformed into educational resources for medical immunology. AI has changed traditional teaching models of medical immunology by constructing immersive virtual learning environments, providing personalized adaptive learning paths, and implementing intelligent assessment with real-time feedback. This has significantly enhanced students’ interest and participation in learning immunology, broadened their academic horizons, and cultivated innovative thinking and academic abilities in immunology. However, the AI-powered education in medical immunology faced many challenges, which included insufficient integration of immunology and AI, unresolved technical difficulties, high implementation costs, issues concerning data security and privacy protection, algorithmic bias, and AI hallucinations. In the future, measures such as breaking through key technologies and improving data governance systems will be taken to promote the research and educational innovation of AI in medical immunology.
文章引用：马兴铭. 人工智能赋能医学免疫学：从前沿研究到教育创新[J]. 职业教育发展, 2026, 15(1): 312-321. https://doi.org/10.12677/ve.2026.151043

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