A scoping review on adenomyosis and artificial intelligence

This scoping review aims to explore the intersection of adenomyosis and artificial intelligence (AI) in medical research and practice. Adenomyosis is a gynecological condition characterized by the presence of endometrial tissue within the uterine muscle, often causing pain and heavy menstrual bleeding. Despite its prevalence, the diagnosis and management of adenomyosis remain challenging due to its complex presentation and the limitations of traditional imaging techniques. The integration of AI, including machine learning and deep learning algorithms, has the potential to enhance diagnostic accuracy, personalize treatment plans, and predict patient outcomes. This review will systematically map the existing literature to identify how AI is being utilized in the study of adenomyosis, highlight gaps in current research, and propose directions for future studies. By synthesizing available evidence, this review seeks to provide a comprehensive overview of the role of AI in advancing the understanding and management of adenomyosis.

Publication Details

Journal
Open Science Framework
Published
2025-01-01
DOI
https://doi.org/10.17605/osf.io/9rfek
Primary Topic
Endometriosis Research and Treatment
Type
article
Field-Weighted Citation Impact
0.00
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article

A scoping review on adenomyosis and artificial intelligence

Open Science Framework
Endometriosis Research and Treatment
article

A scoping review on adenomyosis and artificial intelligence

article en

Abstract

This scoping review aims to explore the intersection of adenomyosis and artificial intelligence (AI) in medical research and practice. Adenomyosis is a gynecological condition characterized by the presence of endometrial tissue within the uterine muscle, often causing pain and heavy menstrual bleeding. Despite its prevalence, the diagnosis and management of adenomyosis remain challenging due to its complex presentation and the limitations of traditional imaging techniques. The integration of AI, including machine learning and deep learning algorithms, has the potential to enhance diagnostic accuracy, personalize treatment plans, and predict patient outcomes. This review will systematically map the existing literature to identify how AI is being utilized in the study of adenomyosis, highlight gaps in current research, and propose directions for future studies. By synthesizing available evidence, this review seeks to provide a comprehensive overview of the role of AI in advancing the understanding and management of adenomyosis.

Open Science Framework
Openalex Percentile: Top 47%
Endometriosis Research and Treatment
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