Oct 2026· Zenodo (CERN European Organization for Nuclear Research)
Artificial Intelligence in Healthcare and Education
Abstract
Artificial intelligence (AI) is increasingly proposed as an adjunct to gynecological ultrasonography, including assessment of adnexal masses, endometrial lesions, adenomyosis, uterine leiomyomas, and reproductive imaging. However, model discrimination reported in curated datasets does not automatically establish safety, calibration, transportability, or patient benefit. Objective: To critically evaluate diagnostic opportunities, methodological weaknesses, real-world evidence pathways, and regulatory considerations relevant to AI-assisted gynecological ultrasound. Methods: A focused evidence-informed narrative synthesis considered representative clinical accuracy studies, systematic reviews, reporting standards, and guidance from professional and regulatory bodies through October 2026. The manuscript differentiates published results from proposed future analyses; no de novo database search exhaustiveness, patient recruitment, or pooled meta-analysis is claimed.
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