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.
Artificial Intelligence Leads Endometriosis Patient to a Diagnosis After 12 Years of Pain and Suffering Endometriosis Foundation of America
Artificial intelligence (AI)-based algorithms are being implemented in breast screening to detect breast cancers on mammographic images. We aimed to apply an epidemiological approach to demonstrate how a cancer detection …
Artificial intelligence (AI) is revolutionizing how we practice medicine. In areas where we have traditionally struggled, such as diagnosing endometriosis, AI has significant potential to improve the breadth and accuracy …
Menopause, endometriosis, miscarriage, and female infertility are health issues affecting women worldwide (nearly half the global population). The biomedical literature is human-readable and evergrowing with around 3.5K papers published daily. …