物理化学响应集成相似度测量 (PRISM) 用于以NIR光谱动态评估样本相似度的全面定量视角
Robert C Spiers1, Callan Norby1, John H Kalivas1
1Department of Chemistry, Idaho State University, Pocatello, Idaho 83209, United States.
Analytical chemistry
|August 18, 2023
概括
在分析化学中,量化样品相似性至关重要. 新的物理化学响应集成相似度测量 (PRISM) 有效评估未标记样品的光谱相似度,提高模型概括性和异常值检测.
科学领域:
- 分析化学 分析化学
- 化学测量 化学测量 化学测量
- 频谱学是一种光谱学.
背景情况:
- 在分析化学中,样本相似性对于校准,分类和异常值检测至关重要.
- 量化相似性是一项挑战,特别是在未标记的光谱数据中.
- 现有的方法往往缺乏综合方法来整合光谱和上下文信息.
研究的目的:
- 开发一种使用光谱数据量化样本相似性的新方法,特别是对于未标记的目标样本.
- 引入物理化学响应的综合相似性测量 (PRISM) 以加强相似性评估.
- 证明PRISM在各种分析应用中的实用性.
主要方法:
- 开发了PRISM,一种混合方法,将光谱相似性与上下文信息 (分析内容,模型预测) 整合在一起.
- 将PRISM应用于不同应用领域的四个近红外 (NIR) 数据集.
- 评估了PRISM的预测可靠性,模型更新,异常值检测和矩阵匹配.
主要成果:
- 通过放大光谱的物理化学特性,PRISM有效量化了目标样本和源样本之间的相似性.
- 在预测可靠性,模型通用性,异常值检测和矩阵匹配评估方面证明了PRISM的有效性.
- 对于生物样本和其他受矩阵效应影响的测量系统来说,PRISM是有前途的.
结论:
- PRISM提供了一个强大的样本相似性的定量衡量,整合了光谱和上下文数据.
- 该方法在各种分析化学应用中提高了模型性能和可靠性.
- PRISM的适应性表明它在不同的光谱数据类型和测量系统中具有广泛的适用性.
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