To advance care for women with endometriosis, we must elevate the quality and completeness of surgical treatment. While the skill and experience of the surgeon remain paramount, the assistance of artificial intelligence (AI) is rapidly becoming both possible and necessary, an opportunity that will soon no longer be optional, but essential for achieving optimal outcomes.

Endometriosis, in all its forms, whether deep infiltrating or peritoneal, demands multi-organ, precision-based surgery. Although minimally invasive laparoscopic techniques are widely employed, there is still no universally accepted standard defining what constitutes optimal surgical care for endometriosis.

While advanced endometriosis may be detected through preoperative imaging, peritoneal endometriosis (PE), the most prevalent form, often escapes detection. It remains elusive even in patients with long-standing, symptom-heavy clinical histories. Its non-specific presentation, the absence of reliable biomarkers, and most critically, its subtle, non-pigmented inflammatory morphology frequently led to lesions being missed intraoperatively, even by experienced surgeons. The consequence is residual disease and persistent symptoms, both of which contribute to poor patient outcomes.

Advanced cases of endometriosis often require multi-organ resection, significantly increasing operative time and necessitating the involvement of a multidisciplinary surgical team. Seamless coordination among specialists is essential. Under the leadership of an experienced gynecologic surgeon, the assistance of artificial intelligence (AI) may help accurately identify and completely excise fibrotic disease, restore normal anatomy, and minimize postoperative morbidity.

Artificial intelligence (AI) presents a transformative opportunity to strengthen the entire continuum of care in endometriosis management. By integrating patient-reported symptoms, imaging data, and surgical video, AI holds the potential to enhance surgical procedures - delivering faster, safer, and more personalized care.

This course, led by internationally recognized endometriosis surgeons with expertise in surgical innovation, will explore the full continuum of AI-supported care:

• Preoperative: We will examine how AI-driven tools—leveraging clinical history, pain mapping, hormonal profiles, imaging (ultrasound, MRI), and Enzian classification—can support early diagnosis, risk stratification, and individualized surgical planning, including the identification of cases that require multidisciplinary collaboration.
• Intraoperative: We will explore how computer-augmented vision, lesion recognition, and real-time anatomical tracking, combined with robotic assistance, can serve as an intelligent co-pilot. These technologies help identify occult or subtle lesions, protect critical structures (ureters, bowel, ovarian tissue), and reduce complications—improving both precision and surgical outcomes.
• Postoperative: We will highlight how AI can support recovery optimization through real-time monitoring of bowel and bladder function, predictive alerts for complications, reduced narcotic use, and personalized follow-up via wearable devices and digital platforms.

This course presents a practical and forward-looking vision for embedding AI across every stage of care to raise surgical standards and improve the quality of life for women with endometriosis.