人工智能能力和ERNICA成员的教育需求:多国调查结果
Holger Till1, Hesham Elsayed1, Beate Obermüller1
1Department of Paediatric and Adolescent Surgery, Medical University of Graz, Graz, Austria.
概括
罕见病网络中的临床医生需要更多的人工智能 (AI) 培训. 通过教育解决这个差距可以改善AI在罕见疾病诊断和管理中的整合.
科学领域:
- 医疗保健技术 医疗保健技术 医疗保健技术
- 医疗信息学医学信息学
- 罕见疾病研究研究.
背景情况:
- 人工智能 (AI) 是医疗保健领域的一个变革性技术,特别是在罕见疾病方面.
- 人工智能可以提高诊断准确度和在罕见疾病管理中的知识共享.
- 临床医生需要专门的AI能力来开发和利用基于AI的医疗支持系统.
研究的目的:
- 评估欧洲罕见遗传和先天异常参考网络 (ER-NICA) 成员的AI准备,教育需求和认知.
主要方法:
- 对389名ERNICA成员分发了一份结构化的在线调查,包含22个问题.
- 收集的数据包括人口统计,人工智能意识,当前使用,教育需求,担忧和未来期望.
主要成果:
- 89名成员回答了 (23%),显示了人工智能的知识差距,其中94%缺乏正式培训.
- 48%的人目前使用人工智能应用程序,主要关注的是可靠性 (80%) 和道德 (71%).
- 受访者认为在线课程和网络研讨会是关键的教育需求,55%的受访者预计ERNICA将领导罕见胃肠道疾病的AI教育.
结论:
- 在ERNICA成员中,人工智能理解和培训存在重大差距.
- 专注于实际人工智能应用,伦理和可解释性的定制教育计划至关重要.
- 通过主动建立人工智能能力,ER-NICA可以促进负责任的AI整合到罕见疾病护理中.
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