Endometriosis is a chronic gynecological condition characterized by the presence of endometrial-like tissue outside the uterine cavity. Its diagnosis remains a significant clinical challenge, often delayed by 7 to 12 …
Endometriosis is a common benign gynecologic disease in women of reproductive age, and its manifestations remarkably decrease quality of life. Lactate, as a metabolite, exerts prominent effects across a wide …
Endometriosis (EMs) is a chronic disease affecting millions of women worldwide, yet its pathogenesis remains unclear, and current diagnostic methods are limited. This study based on the EMs dataset from …
This study aims to develop a machine learning-based predictive model for patients with endometriosis, with the goal of precisely identifying key factors and reliable predictive markers that influence live birth …
Accurate diagnosis of pathology from ultrasound images is reliant upon images of a suitable diagnostic quality being acquired. This study aimed to create a novel machine learning model to automatically …
Endometriosis (EMs) is a gynecological disorder characterized by chronic inflammation and an aberrant immune microenvironment. In this study, we integrated the GSE6364 dataset from the GEO database to identify differentially …
Identification and Validation of Lactate-related gene signatures in endometriosis for clinical valuation and immune characterization by WGCNA and machine learning Frontiers
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To explore B cell infiltration-related genes in endometriosis (EM) and investigate their potential as diagnostic biomarkers.
Endometriosis diagnosis is challenging due to non-specific symptoms that overlap with other gynaecological conditions. This study proposes a non-invasive Machine Learning (ML) ‒ based urine test using Attenuated Total Reflection …