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Detection of peritoneal, ovarian, and bowel endometriosis using FTIR spectroscopy and machine learning.

This study evaluated the diagnostic potential of Fourier-transform infrared (FTIR) spectroscopy combined with machine learning for the detection of ovarian, bowel, and peritoneal endometriosis. The Boruta algorithm was applied to …

Published: Nov. 23, 2025, midnight
Extracellular Trap-Related Genes as Potential Diagnostic Biomarkers for Endometriosis.

Endometriosis (EM), a prevalent gynecological disorder in reproductive-age women, lacks reliable noninvasive diagnostic tools. EM may be detected by neutrophil extracellular traps (NETs), which are essential to inflammation and immunological …

Published: Nov. 19, 2025, midnight
Prediction of Periureteral Adhesions by Drop Infusion Pyelography Before Laparoscopic Hysterectomy: A Retrospective Study.

To identify the predictors for periureteral adhesions preoperatively.

Published: Nov. 18, 2025, midnight
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
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
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
Combination of circular RNA-miRNA-mRNA expression profiles and bioinformatic analysis in ovarian endometriosis.

Endometriosis is a mysterious disease that affects 5 %-10 % of the women of reproductive age. Circular RNAs (circRNAs), a type of noncoding RNA, are involved in its progression, yet …

Published: Sept. 15, 2025, midnight
Machine learning prediction of clinical pregnancy in endometriosis patients following fresh IVF/ICSI-ET.

Fresh embryo transfer reduces waiting time and minimizes embryo cryodamage for endometriosis (EM) patients. The current prediction models for fresh embryo transfer outcomes in EM primarily rely on logistic regression, …

Published: Sept. 3, 2025, midnight
Development and validation of a postpartum cardiovascular disease risk prediction model in women incorporating reproductive and pregnancy-related predictors.

Each year, over 700,000 pregnancies occur in the UK, with up to 10% affected by complications such as hypertensive disorders of pregnancy and gestational diabetes mellitus. Pregnancy-related complications and reproductive …

Published: Aug. 29, 2025, midnight
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