Endometriosis is a complex condition affecting 10% of reproductive-age women worldwide, yet its study has long been hindered by the shortcomings of traditional research models. This review aims to propose …
This study is the first to develop and evaluate a machine learning (ML) model for predicting pelvic adhesions based on ultrasound features, utilizing the SHapley Additive Explanations (SHAP) framework for …
Endometriosis (EM) is a chronic inflammatory gynecological disorder characterized by ectopic endometrial-like lesions, where aberrant angiogenesis is a hallmark driving lesion establishment and progression. However, the transcriptional mechanisms underlying pathological …
The study aimed to investigate the roles of endothelin-1 and endothelin receptors in a rat endometriosis model and to demonstrate how bosentan (BOS), an endothelin receptor blocker, could potentially serve …
This study aimed to construct and validate a nomogram for predicting natural pregnancy after hysteroscopy and laparoscopy in patients with tubal infertility and pelvic endometriosis, providing a basis for precise …
Studies indicate that endometriosis (EMs) is associated with inflammation and metabolic abnormalities. The Remnant Cholesterol Inflammatory Index (RCII) concurrently reflects both inflammatory and metabolic status. However, the relationship between RCII …
Three-dimensional (3D) culture systems provide physiologically relevant models that better replicate in vivo cell architecture and function compared to the conventional two-dimensional cultures. In reproductive biology, 3D models of endometrial …
Endometriosis is a common estrogen-dependent disease marked by ectopic endometrial growth. Although the PI3K/AKT and kisspeptin pathways are known to regulate endometrial homeostasis, their interplay in disease progression remains unclear. …
What was done? A review of artificial intelligence (AI) applications for the imaging of uterine fibroids, endometriosis, and adenomyosis. What was found? AI models can assist with the recognition, segmentation, …