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人工智能跨越范围:在遗传咨询研究生课程中整合和利用人工智能和机器学习的观点

Ofir Feuer¹, Kyla Holmes¹, Sarah Kane²

¹Keck Graduate Institute, Claremont, California, USA.

Journal of genetic counseling

|August 5, 2025

概括

遗传咨询项目对将人工智能 (AI) 和机器学习 (ML) 整合到课程中有不同的看法. 领导者强调AI/ML.

科学领域:

基因组医学是基因组医学.
遗传咨询教育遗传咨询教育
医疗保健中的人工智能

背景情况:

人工智能 (AI) 和机器学习 (ML) 在基因组医学中的越来越多的使用需要熟练的劳动力.
在遗传咨询研究生课程 (GCGPs) 中,AI/ML教育的态度和采用情况存在有限的研究.

研究的目的:

调查GCGP领导层对AI/ML整合到课程中的态度,准备和未来计划.
评估AI/ML对遗传咨询中核心能力能力能力的感知影响.

主要方法:

采用了混合方法的方法,包括对GCGP领导人的两次全国调查.
第一阶段收集了15位领导者的定量数据;第二阶段调查了18位受访者,并采访了5位领导者.
在第二阶段使用反射性主题分析来确定关键主题.

主要成果:

尽管经常接触这些技术,但GCGP领导人对整合AI/ML表达了不同的看法.
人工智能/ML被认为对人际关系,心理社会和咨询技能的影响最小,这强调了人类专业知识的价值.
确定的主要主题包括资源,培训需求,动机,障碍以及AI/ML整合的阶段.

结论:

包括资源,培训和指导方针在内的支持对于在遗传咨询教育中有效整合AI/ML至关重要.
建议为遗传咨询制定AI/ML特定的能力框架,以指导工具的开发和传播.
组织,专业协会和专家之间的加强合作对于在遗传咨询中推进AI/ML至关重要.

关键词:

人工智能的人工智能是人工智能.态度和准备的态度和准备.整合的障碍整合的障碍竞争力能力能力能力.课程的发展课程的发展.教育培训需要教育培训需要遗传咨询教育遗传咨询教育遗传咨询研究生课程研究生课程医疗保健技术医疗保健技术医疗保健技术机器学习是机器学习.混合方法研究的研究方法.基于实践的竞争力.项目领导的观点项目领导的观点专题分析专题分析

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