利用机器学习检测白血病类型的基因表达分析

Umid Kumar Dey, Md. Sajjatul Islam
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引用次数: 2

摘要

人类历史上最严重的流行病之一是被称为癌症的致命疾病。有几种类型的癌症,其中最常听到的是白血病。白血病有急性髓性白血病(AML)和急性淋巴细胞白血病(ALL)两种类型,本研究的目的是考虑几个人的基因表达数据,通过使用XGBoost、随机森林分类和人工神经网络这三种机器学习算法来预测他们患的是哪种类型的白血病。在使用算法之前,先使用主成分分析(PCA)对数据集进行降维处理。
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Genetic Expression Analysis To Detect Type Of Leukemia Using Machine Learning
One of the worst epidemics in the history of mankind is the deadly disease known as cancer. There are several types of cancer and the one that is more commonly heard of these days is leukemia. There are two types of leukemia – acute myeloid leukemia (AML) and acute lymphocytic leukemia (ALL) – and the purpose of this study is to take into account the gene expression data of several people and predict what type of leukemia they have by using three machine learning algorithms, XGBoost, Random Forest Classification and Artificial Neural Networks. The dataset’s dimensionality was reduced using principal component analysis (PCA) before using the algorithms on them.
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