在实验室医学中严格验证机器学习:指导改善质量的指导
Hunter A Miller1, Roland Valdes1
1Department of Pathology and Laboratory Medicine, University of Louisville, Louisville, KY, USA.
Critical reviews in clinical laboratory sciences
|April 18, 2025
概括
人工智能 (AI) 和机器学习 (ML) 可以增强实验室医学中的预测建模. 然而,确保质量保证和适当的验证对于可靠的ML模型开发和应用至关重要.
科学领域:
- 实验室医学 实验室医学
- 人工智能的人工智能是人工智能.
- 机器学习 机器学习
背景情况:
- 人工智能 (AI) 和机器学习 (ML) 为实验室医学中的预测建模提供了变革性的潜力.
- 当前的ML研究往往缺乏必要的质量保证,影响模型的可靠性.
- 分析变化和预分析错误等因素可能会影响临床环境中的ML模型性能.
研究的目的:
- 突出在实验室医学中对ML分类模型的质量改进和验证的必要性.
- 为研究人员,审稿人和编辑提供关键概念,用于开发强大的ML模型.
- 为ML在病理学和实验室医学中的应用适应现有的预测建模指南.
主要方法:
- 关于ML原则和当前指南建议的概述.
- 讨论实验室医学中应用ML的优点和陷.
- 在监管框架内,在临床试验验证和ML模型验证之间进行并行.
主要成果:
- 确定影响ML模型稳定性的关键因素,包括分析和生理变量.
- 强调分类性能指标,模型可解释性和数据质量的重要性.
- 加强对基于机器学习的研究的期刊提交要求的建议.
结论:
- 适当的验证和质量保证对于ML在实验室医学中的可靠应用至关重要.
- 调整现有的指导方针,专注于数据质量,可解释性和性能指标将加强ML模型的开发.
- 讨论的原则不仅适用于实验室医学,也适用于更广泛的生物医学科学研究.
相关概念视频
Uncertainty in Measurement: Accuracy and Precision
Scientists typically make repeated measurements of a quantity to ensure the quality of their findings and to evaluate both the precision and the accuracy of their results. Measurements are said to be precise if they yield very similar results when repeated in the same manner. A measurement is considered accurate if it yields a result that is very close to the true or the accepted value. Precise values agree with each other; accurate values agree with a true value.
Improving Translational Accuracy
Base complementarity between the three base pairs of mRNA codon and the tRNA anticodon is not a failsafe mechanism. Inaccuracies can range from a single mismatch to no correct base pairing at all. The free energy difference between the correct and nearly correct base pairs can be as small as 3 kcal/ mol. With complementarity being the only proofreading step, the estimated error frequency would be one wrong amino acid in every 100 amino acids incorporated. However, error frequencies observed in...
Improving Translational Accuracy
Base complementarity between the three base pairs of mRNA codon and the tRNA anticodon is not a failsafe mechanism. Inaccuracies can range from a single mismatch to no correct base pairing at all. The free energy difference between the correct and nearly correct base pairs can be as small as 3 kcal/ mol. With complementarity being the only proofreading step, the estimated error frequency would be one wrong amino acid in every 100 amino acids incorporated. However, error frequencies observed in...
Controls in Experiments
When conducting an experiment, it is crucial to have control to reduce bias and accurately measure the dependent variables. It also marks the results more reliable. Controls are elements in an experiment that have the same characteristics as the treatment groups but are not affected by the independent variable. By sorting these data into control and experimental conditions, the relationship between the dependent and independent variables can be drawn. A randomized experiment always includes a...
Systematic Error: Methodological and Sampling Errors
In the case of systematic errors, the sources can be identified, and the errors can be subsequently minimized by addressing these sources. According to the source, systematic errors can be divided into sampling, instrumental, methodological, and personal errors.
Sampling errors originate from improper sampling methods or the wrong sample population. These errors can be minimized by refining the sampling strategy. Defective instruments or faulty calibrations are the sources of instrumental...
Sampling errors originate from improper sampling methods or the wrong sample population. These errors can be minimized by refining the sampling strategy. Defective instruments or faulty calibrations are the sources of instrumental...
Introduction to Statistical Process Control
Statistical Process Control (SPC) is a method used to monitor and control quality within processes, particularly in manufacturing and service delivery, by employing statistical methods. SPC aims to distinguish between natural (common cause) variation and variation due to specific changes or events (special cause), allowing for timely improvements and sustained quality. The control chart, a pivotal tool in SPC, visually displays data over time alongside a central line of upper and lower control...


