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Using a Machine Learning Approach to Identify Key Prognostic Molecules for Esophageal Squamous Cell Carcinoma

2021-03-15

Abstract excerpt

<h4>Objective: </h4> A plethora of prognostic biomarkers for esophageal squamous cell carcinoma (ESCC) that have hitherto been reported are challenged with low reproducibility due to high molecular heterogeneity of ESCC. The purpose of this study is to identify the optimal biomarkers for ESCC using machine learning algorithms. <h4>Methods: </h4> Biomarkers related to clinical survival, recurrence or therapeutic re...

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Literature Corpus work
c048964b-7ce8-5b6a-8ac4-6bf7c41a3395
DOI
10.21203/rs.3.rs-310517/v1
Open publication

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Using a Machine Learning Approach to Identify Key Prognostic Molecules for Esophageal Squamous Cell CarcinomaDOI 10.21203/rs.3.rs-310517/v1
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