Classification of colorectal primer carcinoma from normal colon with mid-infrared spectra

IF 2.3 4区 化学 Q1 SOCIAL WORK Journal of Chemometrics Pub Date : 2024-03-13 DOI:10.1002/cem.3542
B. Borkovits, E. Kontsek, A. Pesti, P. Gordon, S. Gergely, I. Csabai, A. Kiss, P. Pollner
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Abstract

In this project, we used formalin-fixed paraffin-embedded (FFPE) tissue samples to measure thousands of spectra per tissue core with Fourier transform mid-infrared spectroscopy using an FT-IR imaging system. These cores varied between normal colon (NC) and colorectal primer carcinoma (CRC) tissues. We created a database to manage all the multivariate data obtained from the measurements. Then, we applied classifier algorithms to identify the tissue based on its yielded spectra. For classification, we used the random forest, a support vector machine, XGBoost, and linear discriminant analysis methods, as well as three deep neural networks. We compared two data manipulation techniques using these models and then applied filtering. In the end, we compared model performances via the sum of ranking differences (SRD).

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利用中红外光谱对结肠癌和正常结肠进行分类
在该项目中,我们使用福尔马林固定石蜡包埋(FFPE)组织样本,利用傅立叶变换中红外光谱成像系统测量每个组织核的数千个光谱。这些组织核介于正常结肠(NC)和结直肠癌(CRC)组织之间。我们创建了一个数据库来管理从测量中获得的所有多元数据。然后,我们应用分类器算法,根据其产生的光谱来识别组织。在分类过程中,我们使用了随机森林、支持向量机、XGBoost 和线性判别分析方法,以及三种深度神经网络。我们使用这些模型比较了两种数据处理技术,然后进行了过滤。最后,我们通过排名差异总和(SRD)对模型性能进行了比较。
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来源期刊
Journal of Chemometrics
Journal of Chemometrics 化学-分析化学
CiteScore
5.20
自引率
8.30%
发文量
78
审稿时长
2 months
期刊介绍: The Journal of Chemometrics is devoted to the rapid publication of original scientific papers, reviews and short communications on fundamental and applied aspects of chemometrics. It also provides a forum for the exchange of information on meetings and other news relevant to the growing community of scientists who are interested in chemometrics and its applications. Short, critical review papers are a particularly important feature of the journal, in view of the multidisciplinary readership at which it is aimed.
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