Latest Articles

Publication Date
Development of an AI-based magnetic resonance imaging reading support program (AMP) for deep endometriosis diagnosis.

Diagnosis of endometriosis faces significant challenges including diagnostic delay and reliance on invasive procedures. Deep endometriosis (DE) poses additional difficulties in non-invasive diagnosis due to its subtle and complex imaging …

Published: Dec. 8, 2025, midnight
AI-Driven Advances in Women's Health Diagnostics: Current Applications and Future Directions.

Background: Women's health has historically served as an incubator for major medical innovations yet often faces relative neglect in sustained funding and implementation. The rise of artificial intelligence (AI) and …

Published: Dec. 3, 2025, midnight
Integrating inflammatory biomarkers and demographic variables with machine learning to predict endometriosis risk.

This study explores the relationship between inflammatory biomarkers and the risk of endometriosis, aiming to develop a predictive model using National Health and Nutrition Examination Survey (1999-2006) data. The dataset …

Published: Nov. 27, 2025, midnight
Closing the evidence loop-membrane-lipid homeostasis and vesicular transport link DEHP exposure to endometriosis.

The causal bridge from environmental exposure to endometriosis (Ems) biology remains incompletely defined. Di(2-ethylhexyl) phthalate (DEHP) is repeatedly implicated in elevated Ems risk, yet actionable molecular anchors linking exposure to …

Published: Nov. 27, 2025, midnight
Urine and Serum miRNA Signatures for the Non-Invasive Diagnosis of Adenomyosis: A Machine Learning-Based Pilot Study.

Background: Adenomyosis remains difficult to diagnose non-invasively due to clinical overlap with endometriosis and the limited specificity of imaging techniques. This pilot study evaluated whether serum- and urine-derived microRNA (miRNA) …

Published: Nov. 26, 2025, midnight
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
Serum miRNA-based diagnostic models for endometriosis: from discovery to validation.

Can a serum miRNA signature serve as a potential diagnostic biomarker for endometriosis (END)?

Published: Nov. 21, 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
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
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
Link copied to clipboard!
Subscribe to Our Newsletter

Stay updated with our latest articles!