{"paper_id":"4f623e7b-91ad-4ab3-b527-f1f275f08f63","body_text":"What was done? A review of artificial intelligence (AI) applications for the imaging of uterine fibroids, endometriosis, and adenomyosis. What was found? AI models can assist with the recognition, segmentation, and localization of uterine fibroids, and the differentiation of benign fibroids and sarcomas. Models can aid in the diagnosis of adenomyosis and endometriosis, and the prediction of the impact of endometriosis on fertility. What the findings mean? Deployed thoughtfully, AI tools could reduce variability, shorten read times, and add objective measurements to routine care. Studies evaluating these models are limited by single-institution designs and continued reliance on expert sonologists and radiologists.\nArtificial Intelligence in Gynecologic Imaging\nPlain Language SummaryThis review explores how artificial intelligence (AI) can enhance imaging for uterine fibroids, endometriosis, and adenomyosis. AI models show promise in identifying, segmenting, and locating uterine fibroids, distinguishing between benign fibroids and sarcomas, diagnosing adenomyosis and endometriosis, and predicting endometriosis's impact on fertility. Thoughtful deployment of AI tools could standardize imaging, reduce reading times, and provide objective measurements in routine care. However, current studies are limited by single-institution designs and still depend heavily on expert sonologists and radiologists, indicating a need for broader, multi-institutional research to validate these AI applications.\nText is machine generated and may contain inaccuracies. FAQ","source_license":"CC0","license_restricted":false}