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The goal of this observational study is to develop and validate artificial intelligence (AI)-based algorithms that support ultrasound diagnosis of endometriosis, adenomyosis, myometrial masses, uterine malformations, and impaired endometrial receptivity in women aged 18-45 years. The main questions it aims to answer are: Can AI algorithms, applied to standardized transvaginal ultrasound images, accurately detect and classify endometriosis and adenomyosis in real time during routine examination? Can AI-based ultrasound assessment predict the histological dignity of myometrial masses, and the likelihood of successful assisted reproduction (AR/IVF) outcome from endometrial features? Participants attending the Department of Obstetrics and Gynecology, Semmelweis University, with clinical suspicion of endometriosis or adenomyosis, a confirmed myometrial mass scheduled for surgery, a suspecte
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