Artificial Intelligence in the Management of Women with Endometriosis and Adenomyosis: Can Machines Ever Be Worse than Humans?

Giulia Emily Cetera, Alberto Eugenio Tozzi, Valentina Chiappa, Isabella Castiglioni, Camilla Erminia Maria Merli, Paolo Vercellini
2024 · doi:10.20944/preprints202403.0956.v1 · W4392966793
preprint OA: green CC0 ⤵ 1 in-corpus citation
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⚙ AI-generated summary by claude@2026-06, 2026-06-06 ⓘ

This review assesses the state of AI in endometriosis and adenomyosis management, finding it can enhance efficiency, surgical outcomes, research, and decision support while acknowledging data quality and professional concerns.

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Abstract

Artificial intelligence (AI) is experiencing advances and integration in all medical specializations, and this creates excitement but also concerns. This narrative review aims at a critical assessment of the state of the art of AI in the field of endometriosis and adenomyosis. By enabling automation, AI may speed up some routine tasks, decreasing gynecologists’ risk of burnout, as well as enabling them to spend more time interacting with their patients, increasing their efficiency and patients’ perception of being taken care of. Surgery may also benefit from AI, especially through its integration with robotic surgery systems. This may improve the detection of anatomical structures and enhance surgical outcomes by combining intra-operative findings with pre-operative imaging. Not only, AI promises to improve the quality of care by facilitating clinical research and through the introduction of decision support tools that can enhance diagnostic assessment and predict treatment effectiveness and side effects, as well as reproductive prognosis and cancer risk. However, concerns exist regarding the fact that good quality data used in tool development and compliance with data sharing guidelines are crucial. Also, professionals are worried AI may render certain specialists obsolete. This said, AI is more likely to become a well-liked team member rather than a usurper.

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Condition tags

endometriosisadenomyosis

Citation neighborhood

Papers in the corpus that this work cites (lower rings, blue) and that cite this one (upper rings, green). Dot size scales with the paper's in-corpus citation count — bigger dot = more influential within the endo/adeno field. Click a dot to open that paper. [ expand to 2 hops ] — adds papers reached through this work's immediate citers/citees. Heavier; up to 60 extra dots.

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europepmc
last seen: 2026-06-04T01:45:00.660873+00:00
openalex
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License: CC0 · commercial use OK