Research Progress on Recurrence Indicators of Endometriosis

In: Journal of Artificial Intelligence and Information · 2026 · vol. 8(6) , pp. 215–219 · doi:10.66069/ojspub.20542241 · W7166677194
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Abstract

Endometriosis (EMS) is a refractory gynecological disease with a high recurrence rate. Its clinical symptoms are mainly dysmenorrhea and infertility, showing diverse manifestations. Due to the atypical clinical symptoms and low specificity of diagnostic markers, the recurrence of EMS cannot be detected in time, which puts great pressure on patients both physically and mentally. Moreover, neither single clinical symptoms nor serological examinations can accurately diagnose the recurrence of EMS, and laparoscopic examination, as the gold standard for diagnosis, is an invasive examination. Therefore, it is urgent to find a prediction scheme with high sensitivity and specificity. Although some studies have shown that certain progress has been made in the diagnostic models of EMS, there is still a lack of systematic review of high - precision prediction models for the recurrence of EMS in the postoperative population. This review systematically summarizes the advantages and disadvantages of various single detection indicators, and at the same time sorts out and summarizes the combined detection models of serological markers and digital prediction models, providing reference for predicting risk factors in the research of the EMS recurrence system.
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Research Progress on Recurrence Indicators of Endometriosis DOI: https://doi.org/10.66069/ojspub.20542241Keywords: Endometriosis, Prediction, RecurrenceAbstract Endometriosis (EMS) is a refractory gynecological disease with a high recurrence rate. Its clinical symptoms are mainly dysmenorrhea and infertility, showing diverse manifestations. Due to the atypical clinical symptoms and low specificity of diagnostic markers, the recurrence of EMS cannot be detected in time, which puts great pressure on patients both physically and mentally. Moreover, neither single clinical symptoms nor serological examinations can accurately diagnose the recurrence of EMS, and laparoscopic examination, as the gold standard for diagnosis, is an invasive examination. Therefore, it is urgent to find a prediction scheme with high sensitivity and specificity. Although some studies have shown that certain progress has been made in the diagnostic models of EMS, there is still a lack of systematic review of high - precision prediction models for the recurrence of EMS in the postoperative population. This review systematically summarizes the advantages and disadvantages of various single detection indicators, and at the same time sorts out and summarizes the combined detection models of serological markers and digital prediction models, providing reference for predicting risk factors in the research of the EMS recurrence system. Downloads Published How to Cite Issue Section License Copyright (c) 2026 Wanting Wang, Fei Li This work is licensed under a Creative Commons Attribution-NoDerivatives 4.0 International License. Deprecated: json_decode(): Passing null to parameter #1 ($json) of type string is deprecated in /www/bryanhousepub/ojs/plugins/generic/citations/CitationsPlugin.inc.php on line 49

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