Endometriosis is a chronic inflammatory disease with impacts on reproduction, health and quality of life, yet its diagnosis is often delayed. Ovarian endometrioma (OMA) is the most common subtype of …
Endometriosis is a chronic condition characterized by the presence of endometrial-like tissue outside the uterine cavity. It affects ~10% of reproductive-aged individuals and is associated with dysmenorrhea and infertility. Although …
Endometriosis (EMs) and recurrent miscarriage (RM) represent major reproductive health challenges. This study investigates the involvement of endothelial-mesenchymal transition (EndMT) in these conditions through integrative bioinformatics analysis, focusing on the …
Background: Deep infiltrating endometriosis (DIE) frequently affects the posterior pelvic compartment, where accurate non-invasive imaging is essential for diagnosis and surgical planning. Aim: This systematic review evaluates the diagnostic performance …
Performing Endometriosis is an autopathographic piece, written and performed by VR and directed by MM (coauthors of the present article). Divided into very short scenes (called Glimpses), Performing Endometriosis is …
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 …
Minimally invasive gynecologic surgery (MIGS) has changed gynecologic care over the past thirty years by introducing techniques like multiport laparoscopy, robotic-assisted laparoscopy, and single-site surgery. MIGS offers advantages like reduced …
To identify the factors influencing postoperative recurrence in endometriosis patients after laparoscopic surgery and to evaluate their clinical predictive performance for postoperative recurrence.
Background and Objectives: Endometriosis, a complex and often underdiagnosed gynecological condition, frequently manifests with ovarian involvement, posing significant clinical challenges. Current diagnostic protocols primarily rely on invasive techniques, thus highlighting …
To develop a machine learning method for the automatic recognition of endometriosis lesions during laparoscopic surgery and evaluate its feasibility and performance.