在 Sysmex XN 系列血液分析仪上使用机器学习模型建立血小板荧光计数法的反射测试规则。

IF 2.2 4区 医学 Q3 HEMATOLOGY
Zhengyu Zhou, Mengqiao Guo, Kang Wu, Zhanyi Yue
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引用次数: 0

摘要

简介血小板荧光计数法(PLT-F)是在 Sysmex XN 系列全自动血液分析仪上对血小板阻抗计数法(PLT-I)进行初步测试后,在临床实践中作为一种反射测试方法使用的。我们的目的是结合 Sysmex XN 系列自动血液分析仪 "CBC + DIFF "模式提供的多个参数,为 PLT-F 方法建立反射测试规则:我们测试了 120 份样本,以评估 PLT-F 和 PLT-I 方法之间的基线偏差。然后,我们选择了 1256 个样本,使用七种机器学习模型(决策树、随机森林、神经网络、逻辑回归、k-近邻、支持向量机和 Naive Bayes)建立并测试反射测试规则。训练集和测试集的比例为 7:3。我们使用各种指标评估了机器学习模型在测试集上的表现,以选出最有价值的模型:结果:PLT-F 方法与 PLT-I 方法具有高度相关性(r = 0.998)。随机森林模型是最有价值的模型,其准确率为 0.893,曲线下面积为 0.954,F1 分数为 0.771,召回率为 0.719,精确度为 0.831,特异性为 0.950。随机森林模型中最重要的变量是平均细胞体积,权重为 15.09%:随机森林模型在我们的研究中表现出很高的效率,可用于为 Sysmex XN 系列全自动血液分析仪建立基于 PLT-F 方法的 PLT 反射检验规则。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Establishing reflex test rules for platelet fluorescent counting method using machine learning models on Sysmex XN-series hematology analyzer

Introduction

The platelet fluorescent counting (PLT-F) method is utilized as a reflex test method following the initial test of the platelet impedance counting (PLT-I) method in clinical practice on the Sysmex XN-series automated hematology analyzer. Our aim is to establish reflex test rules for the PLT-F method by combining multiple parameters provided by the “CBC + DIFF” mode of the Sysmex XN-series automated hematology analyzer.

Methods

We tested 120 samples to evaluate the baseline bias between the PLT-F and PLT-I methods. Then, we selected 1256 samples to establish and test reflex test rules using seven machine learning models (decision Tree, random forest, neural network, logistic regression, k-nearest neighbor, support vector machine, and Naive Bayes). The training set and test set were divided at a ratio of 7:3. We evaluated the performance of machine learning models on the test set using various metrics to select the most valuable model.

Results

The PLT-F method exhibited a high degree of correlation with the PLT-I method (r = 0.998). The random forest model emerged as the most valuable, boasting an accuracy of 0.893, an area under the curve of 0.954, an F1 score of 0.771, a recall of 0.719, a precision of 0.831, and a specificity of 0.950. The most important variable in the random forest model was mean cell volume, weighted at 15.09%.

Conclusion

The random forest model, which demonstrated high efficiency in our study, can be used to establish PLT reflex test rules based on the PLT-F method for the Sysmex XN-series automated hematology analyzer.

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来源期刊
CiteScore
4.50
自引率
6.70%
发文量
211
审稿时长
6-12 weeks
期刊介绍: The International Journal of Laboratory Hematology provides a forum for the communication of new developments, research topics and the practice of laboratory haematology. The journal publishes invited reviews, full length original articles, and correspondence. The International Journal of Laboratory Hematology is the official journal of the International Society for Laboratory Hematology, which addresses the following sub-disciplines: cellular analysis, flow cytometry, haemostasis and thrombosis, molecular diagnostics, haematology informatics, haemoglobinopathies, point of care testing, standards and guidelines. The journal was launched in 2006 as the successor to Clinical and Laboratory Hematology, which was first published in 1979. An active and positive editorial policy ensures that work of a high scientific standard is reported, in order to bridge the gap between practical and academic aspects of laboratory haematology.
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