Oocyte Quality in Endometriosis and the Potential Role of Artificial Intelligence Assessment: A Scoping Review Protocol

Objective: To map the literature on oocyte quality assessment in assisted reproduction technologies (ART) through three complementary perspectives, namely the biological and clinical relationship between endometriosis and oocyte competence, AI-based approaches for oocyte assessment in ART, and AI applications in ART cohorts characterized by endometriosis, in order to explore how these perspectives converge in the literature. Introduction: Evidence on the relationship between endometriosis and oocyte competence remains heterogeneous, while AI-based methods are increasingly being explored in ART to support more objective and reproducible assessment. Given the interdisciplinary nature of the topic, this review approaches the same problem from three complementary perspectives: a biological-clinical perspective, a technical-methodological perspective, and an integrative perspective focusing on their convergence in ART settings. Inclusion criteria: This review will include human evidence sources in ART contexts falling into one or more evidence streams: Stream A, endometriosis and oocyte competence and non-AI studies assessing oocyte quality or oocyte-related outcomes in endometriosis-defined cohorts; Stream B, AI for oocyte assessment and AI applied to oocyte-related data in ART regardless of endometriosis status; Stream C, AI studies in ART settings involving endometriosis-defined cohorts, AI studies in ART cohorts where endometriosis is used, with outcomes that may be clinical or embryo-related. Methods: A three-step search strategy will be used across MEDLINE (PubMed), Scopus, Web of Science and IEEE Xplore. Three complementary search strands aligned to Streams A–C will be executed and deduplicated. Two independent reviewers will screen, assign one or more stream tags, and chart data using a standardized extraction form. Results will be presented as descriptive evidence mapping with tables and figures (including an intersection matrix); the selection process will be reported using a PRISMA flow diagram.