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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
Inflammasomes meet organoids and artificial intelligence: unraveling the complexity of gynecological inflammation.

Gynecological diseases represent a persistent global health burden. According to a WHO report, the global incidence of gynecological diseases exceeds 65%. Furthermore, over 90% of women suffer from gynecological issues …

Published: April 17, 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
Integration of Raman tweezers and machine learning for label-free single-cell characterization of endometriosis cells.

Endometriosis occurs when endometrial tissue grows outside the uterus, affecting millions of women worldwide. Despite extensive research, its cellular mechanisms remain unclear, complicating both diagnosis and treatment. This study presents …

Published: Feb. 19, 2026, midnight
FTIR Spectroscopy Combined with Machine Learning Reveals Molecular Signatures Distinguishing three Phenotypes of Endometriosis.

Endometriosis is a chronic inflammatory disorder in which endometrial tissue grows outside the uterus, leading to pelvic pain and infertility. It remains a major challenge in women's health due to …

Published: Jan. 5, 2026, midnight
Vascular graph network for ovarian lesion classification using optical-resolution photoacoustic microscopy.

Diagnosing ovarian lesions is challenging because of their heterogeneous clinical presentations. Some benign ovarian conditions, such as endometriosis, can have features that mimic cancer. We use optical-resolution photoacoustic microscopy (OR-PAM) …

Published: Dec. 30, 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
Artificial intelligence applications in endometriosis imaging.

Artificial intelligence (AI) may have the potential to improve existing diagnostic challenges in endometriosis imaging. To better direct future research, this descriptive review summarizes the general landscape of AI applications …

Published: April 1, 2025, midnight
BCL6 (B-cell lymphoma 6) expression in adenomyosis, leiomyomas and normal myometrium.

Adenomyosis and leiomyomas are common benign uterine disorders characterized by abnormal cellular proliferation. The BCL6 protein, a transcriptional repressor implicated in cell proliferation and oncogenesis, has been linked to the …

Published: Feb. 4, 2025, midnight
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