Analysis of diagnostic apoptosis-related biomarkers and immune cell infiltration characteristics in endometriosis by integrating bioinformatics and machine learning.
Endometriosis (EMs) is a chronic disease affecting millions of women worldwide, yet its pathogenesis remains unclear, and current diagnostic methods are limited. This study based on the EMs dataset from …
Red blood cell indices as predictor for severity of endometriosis.
Endometriosis is the presence of endometrial tissue outside of the uterine cavity. Certain markers have been used to evaluate the severity of endometriosis. This study aimed to explore the correlation …
Development and validation of a machine learning-based predictive model for live birth outcomes following fresh embryo transfer in patients with endometriosis.
This study aims to develop a machine learning-based predictive model for patients with endometriosis, with the goal of precisely identifying key factors and reliable predictive markers that influence live birth …
[Risk Factors for Recurrence and Their Predictive Value in Endometriosis Patients After Laparoscopic Surgery].
To identify the factors influencing postoperative recurrence in endometriosis patients after laparoscopic surgery and to evaluate their clinical predictive performance for postoperative recurrence.
Combination of circular RNA-miRNA-mRNA expression profiles and bioinformatic analysis in ovarian endometriosis.
Endometriosis is a mysterious disease that affects 5 %-10 % of the women of reproductive age. Circular RNAs (circRNAs), a type of noncoding RNA, are involved in its progression, yet …