Latest Articles

Publication Date
Single-cell profiling and machine learning identify cuproptosis-related fibroblast subpopulations and fibrogenesis modulator AEBP1 in endometriosis.

Endometriosis is characterized by progressive fibrosis and limited therapeutic options. Cuproptosis, a copper-dependent form of regulated cell death, has been implicated in multiple pathological conditions, but its relevance to fibroblast-mediated …

Published: May 18, 2026, midnight
HSD11B1 suppresses ferroptosis in endometrial stromal cells through the JUND/IL-10 axis to promote endometriosis progression.

Endometriosis (EMs) is a common gynecological disorder characterized by ectopic endometrial tissue growth, leading to chronic inflammation and pelvic pain. Despite its high prevalence, the molecular mechanisms underlying EMs remain …

Published: May 18, 2026, midnight
A multi-dimensional computational screening strategy for rapid identification of active components from traditional chinese medicine: Validation and application in Liangdi decoction against endometriosis.

This study aims to develop and validate a Multi-Dimensional Computational Screening (MDCS) strategy to identify bioactive components by jointly considering target affinity, exposure potential, and safety, using Liangdi decoction (LDD) …

Published: May 8, 2026, midnight
Bridging the Gap Between Artificial Intelligence and Clinical Readiness in Endometriosis Diagnosis: A Systematic Review.

To systematically evaluate the methodological quality and diagnostic performance of artificial intelligence (AI) applications, specifically machine learning (ML) and deep learning (DL), in the diagnosis of endometriosis through imaging and …

Published: April 30, 2026, midnight
Single-Cell Transcriptomic Profiling and Machine Learning Integration Unveil Stromal Cell Heterogeneity in Endometriosis.

Endometriosis (EMs) affects approximately 10% of reproductive-age women worldwide, yet its pathogenesis remains incompletely understood. Abnormal cell differentiation and somatic mutations in the ectopic endometrial microenvironment play critical roles in …

Published: April 23, 2026, midnight
A Combined Transcriptomic and Machine Learning Study Reveals PAX8 as a Promising Diagnostic Biomarker in Endometriosis.

Endometriosis (EM) is a chronic, estrogen-dependent disease that lacks reliable noninvasive diagnostic biomarkers. This study was aimed at evaluating the diagnostic value of PAX8 using integrated transcriptomic and machine learning …

Published: April 17, 2026, midnight
LRP1 as a potential diagnostic and immunomodulatory target in endometriosis: evidence from multi-omics and single-cell analyses.

Endometriosis (EMS) is a common gynecological disease that seriously affects women's health and quality of life. However, the detailed dynamic cellular and molecular mechanisms underlying EMS pathogenesis remain largely unknown. …

Published: April 15, 2026, midnight
Non-invasive endometriosis staging prediction using integrated radiomics and spatiotemporal transformer model based on dynamic contrast-enhanced MRI.

Precise staging of endometriosis remains a clinical challenge, as current diagnosis depends almost entirely on laparoscopic visualization-an invasive procedure marked by considerable inter-observer disagreement and diagnostic delays. Existing non-invasive approaches, …

Published: April 9, 2026, midnight
SUPT16H Overexpression Alleviates the Progression of Endometriosis and Systemic Lupus Erythematosus by Regulating Oxidative Stress.

To screen immune-related biomarkers in diagnosing patients with both endometriosis (EM) and systemic lupus erythematosus (SLE).

Published: April 4, 2026, midnight
Study on material basis and network mechanism of the Guizhi Fuling pills in the treatment of endometriosis and endometrial polyps.

To explore the material basis and network mechanism of the Guizhi Fuling pills in the treatment of endometriosis and endometrial polyps based on network pharmacology and machine learning. The effective …

Published: April 4, 2026, midnight
Link copied to clipboard!
Subscribe to Our Newsletter

Stay updated with our latest articles!