Identification and verification of diagnostic biomarkers for deep infiltrating endometriosis based on machine learning algorithms

Abstract excerpt

This study addresses the challenges in the early diagnosis of deep infiltrating endometriosis (DIE) by exploring the potential role of the deubiquitinating enzyme USP14. By analyzing the GSE141549 dataset from the Gene Expression Omnibus (GEO) database, using bioinformatics methods and three machine learning algorithms (LASSO, Random Forest, and Support Vector Machine), the key feature gene USP14 was identified....

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