下一代基于患者的实时质量控制模型
Xincen Duan1, Minglong Zhang2, Yan Liu3
1Department of Laboratory Medicine, Zhongshan Hospital, Fudan University Shanghai, Shanghai, China.
Annals of laboratory medicine
|June 5, 2024
概括
基于患者的实时质量控制 (PBRTQC) 利用AI进行测试性能评估. 本综述批判性地比较了人工智能驱动的PBRTQC方法与传统方法,突出了AI.
科学领域:
- 临床化学 临床化学
- 医疗信息学 医疗信息学
- 医疗保健中的人工智能
背景情况:
- 基于患者的实时质量控制 (PBRTQC) 使用患者数据监测实验室测定性能.
- 计算机科学和计算能力的进步推动了PBRTQC算法的开发.
- 人工智能 (AI) 在PBRTQC中得到了快速采用,有望带来显著的优势.
研究的目的:
- 批判性地比较各种PBRTQC算法,包括基于AI的方法.
- 以人工智能驱动的PBRTQC与传统的质量控制方法进行对比.
- 评估在PBRTQC中实施AI的可行性和好处.
主要方法:
- PBRTQC算法的描述和对比:移动平均数,回归调整的实时QC,神经网络和异常检测.
- 基于人工智能的比较分析与传统的PBRTQC技术.
- 对实验室实施相关的AI工具特征的评估.
主要成果:
- 人工智能工具对PBRTQC的可用性,用户友好性和计算效率越来越高.
- 人工智能的传统缺点,如复杂性和高资源需求,正在减少.
- 人工智能为增强PBRTQC提供了有吸引力的解决方案.
结论:
- 基于人工智能的PBRTQC方法比传统技术具有显著的优势.
- 人工智能工具的可访问性和效率越来越高,使其在临床实验室中更容易被采用.
- 人工智能准备通过克服传统方法的局限性来彻底改变PBRTQC.
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