(PDF) Endometrial receptivity profiled through transcriptomic analysis of uterine fluid extracellular vesicles using systems biology and bayesian modeling for pregnancy prediction - researchgate.net
(PDF) Endometrial receptivity profiled through transcriptomic analysis of uterine fluid extracellular vesicles using systems biology and bayesian modeling for pregnancy prediction researchgate.net
Endometrial receptivity profiled through transcriptomic analysis of uterine fluid extracellular vesicles using systems biology and bayesian modeling for pregnancy prediction - Nature
Endometrial receptivity profiled through transcriptomic analysis of uterine fluid extracellular vesicles using systems biology and bayesian modeling for pregnancy prediction Nature
Preoperative prediction of the HER2 status and prognosis of patients with endometrial cancer using multiparametric MRI-based radiomics: a multicenter study - Nature
Preoperative prediction of the HER2 status and prognosis of patients with endometrial cancer using multiparametric MRI-based radiomics: a multicenter study Nature
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 …
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 …
Machine learning prediction of clinical pregnancy in endometriosis patients following fresh IVF/ICSI-ET.
Fresh embryo transfer reduces waiting time and minimizes embryo cryodamage for endometriosis (EM) patients. The current prediction models for fresh embryo transfer outcomes in EM primarily rely on logistic regression, …