Far more complex than merely a single system disorder, endometriosis requires a nuanced, patient-centered approach grounded in multidisciplinary care. Nurses play a vital role in this framework, working collaboratively with …
Background and Objectives: Augmented reality (AR), mixed reality (MR), computer vision, artificial intelligence (AI), and three-dimensional (3D) modeling may be particularly relevant in fertility-preserving gynecologic surgery, where disease must be …
Endometriosis is a chronic inflammatory condition that can result in chronic pain through complex nociceptive, neuropathic, and nociplastic pathways. This article provides a comprehensive background on endometriosis as well as …
Endometriosis is a benign yet chronic gynecologic condition that, in rare cases, may undergo malignant transformation. Although endometriosis-associated malignancies most commonly arise in the ovary, extragonadal sites may also be …
Postoperative pain following laparoscopic surgery can delay recovery and increase opioid use. Lower insufflation pressures have been consistently shown to reduce pain in general surgery procedures, but their impact in …
Perimenopause is a clinically distinct stage in which abnormal uterine bleeding, fibroids, adenomyosis, endometriosis, and adnexal pathology may require surgical evaluation. Management is complex because symptom burden and structural disease …
To compare the quality of AI-generated responses to gynecologic post-operative questions with educational materials published by professional societies.
Deep infiltrating endometriosis predominantly affects the posterior pelvic compartment and often requires complex surgical procedures, which are associated with a significant risk of postoperative complications. Limited evidence is available regarding …
Robot-assisted hysterectomy (RAH) has been progressively introduced in gynecologic surgery, yet nationwide data describing its uptake and early efficiency outcomes remain limited. We described trends in surgical route for hysterectomy …
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).