The Impact of AI on Endometriosis Patient Education: Evaluating Information Quality and Accuracy

Abstract

Objective: The worldwide condition impacts countless women 
suffering from endometriosis, leading to frequent misinterpretations 
and delays in medical evaluations. A study examines how artificial 
intelligence platforms enhance patient education regarding 
endometriosis by providing precise information to patients.
Methods: The study investigated current AI applications within 
patient education platforms, focusing specifically on treatment for 
endometriosis. It analyzed research published between January 2015 
and August 2024. To identify peer-reviewed articles, the research 
employed the databases of PubMed, IEEE Xplore, and Google 
Scholar.
Results: Natural language processing (NLP) and machine learning 
algorithms utilized in AI applications demonstrate success in 
providing relevant educational information customized for patients 
with endometriosis. These platforms have accomplished several 
important goals, such as dispelling misconceptions and enhancing 
patient engagement, while empowering patients with greater control 
over their knowledge related to their condition.
Conclusion: Several issues related to data quality, ambiguous 
algorithms, and privacy concerns continue to impede the 
advancement of AI-driven systems for educating endometriosis 
patients. Healthcare training systems powered by AI offer significant 
enhancements to patient education, which boosts their selfmanagement capabilities concerning the disease.