临床或研究实验室专业人员对人工智能使用的概念化:在墨西哥实施的挑战
Jorge Manuel Sánchez-González1, María Cristina Morán-Moguel2, Antonio Eugenio Rivera-Cisneros3
1Mexican Federation of Clinical Pathology, AC (FEMPAC), Latin American Association of Clinical Pathology and Laboratory Medicine (ALAPAC/ML), National Institute of Learning, Skills and Research in Sciences, SC (INAHIC), Zapopan, Jalisco, Mexico.
EJIFCC
|October 16, 2025
概括
临床实验室专业人员熟悉人工智能 (AI),但缺乏培训,并担心失业. 未来的AI整合需要解决这些问题,并制定有针对性的教育策略.
科学领域:
- 医疗保健技术 技术 医疗保健 技术
- 临床诊断 临床诊断 临床诊断
- 人工智能在医学中的应用
背景情况:
- 人工智能 (AI) 正在改变医疗保健,为诊断,效率和决策提供先进的工具.
- 在临床实验室 (CLs),人工智能集成自动化数据处理,帮助早期发现疾病,并支持个性化医疗.
- 了解员工对CLAI的看法对于识别实施障碍至关重要.
研究的目的:
- 评估墨西哥临床实验室 (CL) 专业人员对人工智能 (AI) 的概念化.
- 确定AI在CL环境中实施AI的挑战和机会.
- 探索专业人士对人工智能的熟悉,使用,关注和感知应用.
主要方法:
- 通过在线调查进行了一项观察性,前性,横截面性,比较性研究.
- 该调查针对墨西哥各地的公共和私营CL专业人士.
- 36个问题收集了社会人口统计数据,并评估了AI的熟悉程度,使用,担忧,局限性和应用.
主要成果:
- 125名男性和237名女性参与;专业人士通常熟悉AI.
- 首选的人工智能应用包括减少预分析错误 (67%) 和节省时间 (65%).
- 主要担忧是缺乏知识/培训 (74%),害怕工作替代 (66%) 和道德方面;只有4.7%的人接受过正式的人工智能培训,但84.8%的人希望这样做.
结论:
- 调查结果表明,需要制定与人工智能相关的公共和教育政策.
- 优先事项包括规范人工智能采用,开发最佳培训策略,并促进道德考虑.
- 努力应确保人工智能实施避免排除特定社会群体.
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