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Machine-learning-derived prediction models of recurrence of ovarian endometriosis after laparoscopic surgery.

Endometriosis is a long-term health problem that affects a significant number of women globally. Among the various forms of endometriosis, ovarian endometriosis (OEM) is the most prevalent. This research aimed …

Published: Nov. 10, 2025, midnight
Machine Learning Model Using CT Radiomics Achieves High Accuracy in Differentiating Malignant and Benign Endometrial Tumors - geneonline.com

Machine Learning Model Using CT Radiomics Achieves High Accuracy in Differentiating Malignant and Benign Endometrial Tumors geneonline.com

Published: Nov. 4, 2025, 1:32 p.m.
CT radiomics-based explainable machine learning model for accurate differentiation of malignant and benign endometrial tumors: a two-center study - BioMedical Engineering OnLine

CT radiomics-based explainable machine learning model for accurate differentiation of malignant and benign endometrial tumors: a two-center study BioMedical Engineering OnLine

Published: Nov. 4, 2025, 11:50 a.m.
Identified endoplasmic reticulum stress-related molecular cluster and immune characterization in endometriosis.

Endometriosis is a common disease among women of childbearing age, and endoplasmic reticulum stress (ERS), a response involved in regulating protein homeostasis, has been linked to its pathogenesis. To identify …

Published: Nov. 4, 2025, midnight
Integrated bioinformatics analysis and machine learning identifies FZD4, SRPX2, and COL8A1 as angiogenesis hub genes in endometriosis.

This study aims to identify angiogenesis-associated genes (AAGs) in endometriosis (EM) by integrating bioinformatics analysis with machine learning, and to investigate their underlying mechanisms. Differentially expressed genes (DEGs) were screened …

Published: Oct. 26, 2025, midnight
Integrative transcriptomic analysis identifies shared EndMT-related gene signatures in endometriosis and recurrent miscarriage.

Endometriosis (EMs) and recurrent miscarriage (RM) represent major reproductive health challenges. This study investigates the involvement of endothelial-mesenchymal transition (EndMT) in these conditions through integrative bioinformatics analysis, focusing on the …

Published: Oct. 21, 2025, midnight
Serum Fingerprinting-Based Integrative Dual-Omics Machine Learning for Endometriosis-Associated Ovarian Cancer.

Dual-omics, by integrating molecular information from two distinct dimensions, can offer more comprehensive perspective for complex disease. Herein, we developed an efficient functionalized mesoporous nanoparticle-coupled laser desorption/ionization mass spectrometry (fMNPLDI-MS) …

Published: Oct. 16, 2025, midnight
Potential biomarkers for early detection of endometriosis: current state of art (what we know so far).

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 …

Published: Oct. 13, 2025, midnight
Identification and validation of lactate-related gene signatures in endometriosis for clinical evaluation and immune characterization by WGCNA and machine learning.

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 …

Published: Oct. 7, 2025, midnight
Analysis of diagnostic apoptosis-related biomarkers and immune cell infiltration characteristics in endometriosis by integrating bioinformatics and machine learning.

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 …

Published: Sept. 29, 2025, midnight
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