| Autor: |
Liu, Quewang, Wang, Yueying, Duan, Meiyu, Fan, Yusi, Pan, Xingyuan, Liu, Shuai, Yu, Qiong, Huang, Lan, Zhou, Fengfeng, Kolesar, Jill Marie |
| Předmět: |
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| Zdroj: |
Diagnostics (2075-4418); Feb2021, Vol. 11 Issue 2, p347-347, 1p |
| Abstrakt: |
The incidence and mortality rates of lung cancers are different between females and males. Therefore, sex information should be an important part of how to train and optimize a diagnostic model. However, most of the existing studies do not fully utilize this information. This study carried out a comparative investigation between sex-specific models and sex-independent models. Three feature selection algorithms and five classifiers were utilized to evaluate the contribution of the sex information to the detection of early-stage lung cancers. Both lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC) showed that the sex-specific models outperformed the sex-independent detection of early-stage lung cancers. The Venn plots suggested that females and males shared only a few transcriptomic biomarkers of early-stage lung cancers. Our experimental data suggested that sex information should be included in optimizing disease diagnosis models. [ABSTRACT FROM AUTHOR] |
| Databáze: |
Complementary Index |
| Externí odkaz: |
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