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Initial results in the automatic visual recognition of endometriosis lesions by artificial intelligence during laparoscopy: a proof-of-concept study.

To develop a machine learning method for the automatic recognition of endometriosis lesions during laparoscopic surgery and evaluate its feasibility and performance.

Published: Sept. 3, 2025, midnight
Effects of Mono- (2-ethylhexyl) phthalate and Phthalic Acid Monobenzyl Ester on endometriosis using network toxicology, machine learning and molecular docking techniques.

Phthalate metabolites Mono- (2-ethylhexyl) phthalate(MEHP) and Phthalic Acid Monobenzyl Ester (MBZP) are widely present in the environment, can interfere with the endocrine system and accumulate in human tissues, and are …

Published: Aug. 8, 2025, midnight
Artificial intelligence-driven decision tree model for predicting quality of life determinants in women with endometriosis.

Endometriosis significantly impacts the quality of life (QoL) of affected women due to its complex symptomatology. This study aimed to develop a decision tree-based model to identify the key determinants …

Published: Aug. 8, 2025, midnight
Uncovering symptom-lesion associations through Machine learning.

to evaluate the association between symptoms and the site of endometriosis lesions using machine learning analysis DESIGN: retrospective study SETTING: Two tertiary hospitals.

Published: Aug. 7, 2025, midnight
Diagnostic Potential of Serum Circulating miRNAs for Endometriosis in Patients with Chronic Pelvic Pain.

Background: Endometriosis is a chronic gynecological condition marked by ectopic endometrial-like tissue, leading to inflammation, pain, and infertility. Diagnosis is often delayed by up to 10 years. Identifying non-invasive biomarkers …

Published: July 21, 2025, midnight
Identification of biomarkers for endometriosis based on summary-data-based Mendelian randomization and machine learning.

Endometriosis (EM) significantly impacts the quality of life, and its diagnosis currently relies on surgery, which carries risks and may miss early lesions. Noninvasive biomarkers are urgently needed for early …

Published: April 8, 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
Characterization of key genes and immune cell infiltration associated with endometriosis through integrating bioinformatics and experimental analyses.

Endometriosis (EM) is the most common gynecological disease in women of childbearing age. This study aims to identify key genes and screen drugs that may contribute to EM treatment.

Published: March 31, 2025, midnight
Association of composite dietary antioxidant index and endometriosis risk in reproductive-age women: a cross-sectional study using big data-machine learning approach.

Endometriosis (EM) is a chronic gynecological disorder characterized by the growth of endometrial-like tissue outside the uterus, leading to pain and infertility. Recent studies suggest that antioxidants may play a …

Published: March 27, 2025, midnight
Unraveling shared diagnostic genes and cellular microenvironmental changes in endometriosis and recurrent implantation failure through multi-omics analysis.

Endometriosis and Recurrent Implantation Failure (RIF) are both pivotal clinical issues within the realm of reproductive medicine, sharing significant overlap in their pathophysiological mechanisms. However, research exploring the commonalities between …

Published: March 17, 2025, midnight
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