Assessing the Influence of Artificial Intelligence on Patient Education for Endometriosis: A Comprehensive Evaluation of Information Quality, Accuracy, and Accessibility

Abstract

Objective: The global situation 
affects numerous women dealing 
with endometriosis, resulting in 
widespread misunderstandings and 
delays in receiving medical assessments. A research study 
investigates how artificial intelligence tools improve patient 
knowledge about endometriosis by delivering accurate information to 
individuals.
Methods: The research explored existing applications of AI in 
patient education platforms, with an emphasis on 
endometriosis treatment. It examined studies released from 
January 2015 to August 2024. To locate peer-reviewed 
publications, the study utilized the databases of PubMed, IEEE 
Xplore, and Google Scholar.
Results: Natural language processing (NLP) and machine 
learning technologies used in AI applications have proven 
effective in delivering tailored educational content for patients 
with endometriosis. These systems have achieved several key 
objectives, including correcting misunderstandings and 
improving patient interaction, while enabling patients to have 
increased authority over their understanding of their 
condition.
Conclusion: Numerous challenges associated with data 
quality, unclear algorithms, and privacy issues persistently 
hinder the progress of AI-based systems aimed at educating 
endometriosis patients. Healthcare training systems supported 
by AI provide substantial improvements in patient education, 
which enhances their ability to manage the disease effectively.