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The predictive value of neural network models and random forest models for the classification of cervical intraepithelial lesions based on gene methylation and HPV infection genotype

2026-05-18

Abstract excerpt

<title>Abstract</title> <p>Objective This study aims to evaluate the application value of neural network (NN) and random forest (RF) models integrating gene methylation markers and HPV infection typing data in the prediction of cervical intraepithelial neoplasia (CIN) grading, providing new tools for the precise screening of clinical cervical cancer. Methods Clinical data of 138 patients with cervical lesions w...

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Literature Corpus work
08e71c0d-f164-57a3-8f03-4088b5c03782
DOI
10.21203/rs.3.rs-9365221/v1
Open publication

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The predictive value of neural network models and random forest models for the classification of cervical intraepithelial lesions based on gene methylation and HPV infection genotypeDOI 10.21203/rs.3.rs-9365221/v1
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