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 …
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 …
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.
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 …
Evaluation of Pyroptosis-Associated Genes in Endometrial Cancer Utilizing a 101-Combination Machine Learning Framework and Multi-Omics Data - Frontiers
Evaluation of Pyroptosis-Associated Genes in Endometrial Cancer Utilizing a 101-Combination Machine Learning Framework and Multi-Omics Data Frontiers