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) …
Endometriosis diagnosis currently relies on invasive laparoscopy, creating a need for non-invasive alternatives. This study evaluates microRNAs (miRNAs) as potential diagnostic biomarkers for endometriosis through systematic evidence synthesis and performance …
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 …
MicroRNAs (miRNAs) have emerged as robust biomarkers for diagnosing and prognosing gynecological diseases due to their disease-specific expression and remarkable stability in body fluids. Despite the inherent instability of RNA …
Objectives: This study aimed to systematically compare the diagnostic accuracy of magnetic resonance imaging (MRI) and transvaginal ultrasound (TVUS) for deep infiltrating endometriosis (DIE) and to evaluate their impact on …
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 …
Rectal endometriosis is a complex condition requiring multidisciplinary treatment. Accurate preoperative assessment is critical for selecting the appropriate surgical technique, with transvaginal ultrasound (TVS) and endorectal ultrasound (ERUS) being key …
Machine Learning Model Using CT Radiomics Achieves High Accuracy in Differentiating Malignant and Benign Endometrial Tumors geneonline.com
Will GDHG stock benefit from AI adoption - Quarterly Trade Report & High Accuracy Swing Entry Alerts Fundação Cultural do Pará
Diagnostic Accuracy of Endometrial Sampling Methods for Determining Histologic Type and Grade in Endometrial Cancer: A Retrospective Cohort Study Cureus