Artificial intelligence as a diagnostic support tool in hysteroscopy: current evidence and clinical implications
AI applied to hysteroscopy shows considerable promise for enhancing diagnostic accuracy, consistency, and intraoperative decision-making. To enable translation into practice, future research should emphasize multicenter collaborations, standardized imaging protocols, external validation, and the development of explainable models that can be trusted in clinical settings.
Authors
- Marcello Ceccaroni (ORCID: https://orcid.org/0000-0002-6797-4876)
- Filippo Alberto Ferrari
- Federico Ferrari
Institutions
- University of Ferrara (IT)
- Churchill Hospital (GB)
- Agostino Gemelli University Polyclinic (IT)
- Ospedale Sacro Cuore Don Calabria (IT)
- University of Clermont Auvergne (FR)
- Fatebenefratelli Hospital (IT)
- Institut de Recherche contre les Cancers de l’Appareil Digestif (FR)
- Fondazione IRCCS Istituto Nazionale dei Tumori (IT)
- Institut de Chirurgie Guidée par l'Image (FR)
- Ospedale San Pietro Fatebenefratelli (IT)
- University of Brescia (IT)
Publication Details
- Journal
- Minimally Invasive Therapy & Allied Technologies
- Published
- 2026-02-23
- DOI
- https://doi.org/10.1080/13645706.2026.2635049
- Primary Topic
- Gynecological conditions and treatments
- Type
- article
- Field-Weighted Citation Impact
- 0.00