Bianca Schor suffered for seven years before being diagnosed with endometriosis. As a disabled woman, she decided to dedicate her scientific career and AI skills to make sure women do not suffer from endometriosis in silence any longer. Bianca holds a PhD in Computer Science from the University of Cambridge, UK, where she focused on designing responsible AI for non-experts, including families, teenagers, and clinicians. Using the latest Deep-learning models, Bianca co-designed AI prototypes for ovarian cancer and endometriosis, and joined Amsterdam UMC as an AI researcher specialising in gynaecological imagery. In 2023, Bianca also founded the first UK’s national “AI for women’s health” academic community, hosted at the Alan Turing Institute in London. In 2025, Bianca was recognised as an AI visionary for her work in this field by the National Health Service (NHS) and Department of Health and Social Care (DHSC) in the UK.

Associate professor Dr. Robert de Leeuw, PhD, is a leading expert in gynecological imaging and AI-driven diagnostics at Amsterdam UMC. As a researcher and clinician, he specializes in using ultrasound imaging, big data, and AI technologies to improve the diagnosis and treatment of gynecological conditions such as endometriosis and adenomyosis . He plays a pivotal role in multiple research projects, including AI-assisted ultrasound diagnostics and mHealth solutions for women’s health . Dr. de Leeuw collaborates extensively with ICT departments, patient organizations, and international experts to bridge the gap between AI innovation and clinical practice, aiming to reduce diagnostic delays and enhance patient outcomes .

Prof. Judith Huirne, MD, PhD, is a renowned gynecologist and expert in ultrasound imaging at Amsterdam UMC. As a pioneer in AI-assisted diagnostics and minimally invasive gynecological treatments, she has played a crucial role in advancing research on endometriosis, adenomyosis, and abnormal uterine bleeding . Prof. Huirne has led numerous high-impact studies and has been instrumental in developing AI-driven solutions for gynecological imaging . She is also actively involved in international collaborations, setting new standards for ultrasound-based diagnostics and treatment strategies. As head of department, she combines clinical expertise with cutting-edge technology to enhance women’s healthcare worldwide .

Dilara is a PhD candidate in the Radiology department at Amsterdam UMC, where her research centers on leveraging deep learning techniques for quantitative MRI to develop personalized cancer treatments. She holds a BSc in Artificial Intelligence and an MSc in Medical Informatics, with a keen interest in computer vision, deep learning, and medical imaging. During her time as a visiting student in Cambridge, Dilara conducted her MSc thesis project on AI-driven automated segmentation in gynecological ultrasound.

Mijs is a PhD student researching the use of artificial intelligence to improve the diagnosis and treatment of endometriosis and adenomyosis. In addition to her PhD research, she is an educator in the Medical Informatics bachelor and master programs, where she teach courses on programming and user experience (UX) research methods for evaluating eHealth solutions as part of the eHealth Living & Learning lab. She has obtained her master degree in Technical Medicine, specializing in medical imaging, which provides her with a strong foundation in both clinical practice and technological innovation.

Mineli is an MPhil student in Population Health Sciences at the University of Cambridge, specialising in the health data science stream. She is taking modules in machine learning and advanced biostatistics to support her dissertation on predictive modeling. Mineli has an interest in the integration of AI and women’s healthcare, aiming to enhance her quantitative and clinical skills in this field. With previous publications in antimicrobial resistance, she is eager to explore the quantitative application of medicine, particularly in advancing women's health.