Chair: Angharad Jones
Faculty: Sophie Strong, Fevzi Shakir, Arvind Vashisht

Artificial Intelligence (AI) is transforming healthcare; and endometriosis care is no exception. AI is revolutionising diagnosis, treatment planning, and data analysis for this complex condition. This course provides a comprehensive overview of how AI technologies can be utilised to improve outcomes in endometriosis care. Participants will explore the role of AI in enhancing diagnostic accuracy, supporting personalised treatment strategies, and fostering collaborative research. By integrating AI-driven insights with clinical expertise, this course aims to equip healthcare professionals with the knowledge to optimise patient care. Without clearly defined criteria for specific management approaches we will highlight the challenges and merits of different surgical approaches for the disease. We focus on multidisciplinary working to improve women’s healthcare together. Learning Objectives: At the end of this course, the participant will be able to: 1) Recognize the wider role of the AI endometriosis care; 2) Establish how AI can assist surgical reporting; and 3) Explain the role of AI to reduce the diagnostic delay in endometriosis care.

COURSE OUTLINE 3:15 pm Welcome, Introduction and Course Overview A. Jones 3:20 pm AI Enabled Early Diagnosis of Endometriosis O. Barnick 3:35 pm The Role of AI in Surgical Reporting of Endometriosis F. Shakir 3:50 pm An Overview of AI Use in Delivering Surgical Management of Endometriosis A. Vashisht 4:05 pm Discussion Questions & Answers 4:15 pm Adjourn