To compare the quality of AI-generated responses to gynecologic post-operative questions with educational materials published by professional societies.
Endometriosis (EM) and chronic endometritis (CE) are both implicated in female infertility, yet the relationship between them remains incompletely understood. In this narrative review, we synthesize non-systematically selected clinical and …
Transvaginal ultrasound (TVUS) is widely used for diagnosing ovarian endometriosis but remains limited by significant operator dependency. This systematic review and meta-analysis evaluated the diagnostic accuracy of ultrasound-based artificial intelligence …
Endometriosis is a common gynecologic condition in which pelvic MRI plays an important role in diagnosis and preoperative assessment. AI-enabled automated uterus segmentation on pelvic MRI could support endometriosis care …
To systematically evaluate the methodological quality and diagnostic performance of artificial intelligence (AI) applications, specifically machine learning (ML) and deep learning (DL), in the diagnosis of endometriosis through imaging and …
To systematically evaluate the task-specific performance and clinical translational readiness of artificial intelligence (AI) applications across the preoperative, intraoperative, and postoperative phases of minimally invasive gynecologic surgery (MIGS).
Gynecological diseases represent a persistent global health burden. According to a WHO report, the global incidence of gynecological diseases exceeds 65%. Furthermore, over 90% of women suffer from gynecological issues …
Endometriosis and polycystic ovary syndrome (PCOS) are common, multifactorial gynecological disorders shaped by endocrine imbalance, immune dysfunction, metabolic disruption, genetic susceptibility, and environmental exposures. Despite their major contribution to infertility …
Endometriosis profoundly impairs sexual function through complex interactions between pain, hormonal disturbances, psychological distress, and sociodemographic factors.