{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"omics_type":["Unknown"],"volume":["15(23)"],"submitter":["Kupec T"],"pubmed_abstract":["<b>Background:</b> 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) profiles, combined with machine-learning approaches, could support non-invasive diagnosis. <b>Methods:</b> Serum and urine samples were collected from 59 patients undergoing surgery for chronic pelvic pain at the Endometriosis Centre of RWTH Aachen University Hospital. Seven patients had isolated adenomyosis, 34 had histologically confirmed endometriosis, and 18 served as negative controls. miRNAs were profiled using next-generation sequencing. A structured feature-selection pipeline (variance filtering, univariate testing, mutual information, rec"],"journal":["Diagnostics (Basel, Switzerland)"],"pagination":["3012"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC12691541"],"repository":["biostudies-literature"],"pubmed_title":["Urine and Serum miRNA Signatures for the Non-Invasive Diagnosis of Adenomyosis: A Machine Learning-Based Pilot Study."],"pmcid":["PMC12691541"],"pubmed_authors":["Stickeler E","Kuo CC","Meyer-Wilmes P","Wittenborn J","Kupec T","Maurer J","Senger R","Najjari L"],"additional_accession":[]},"is_claimable":false,"name":"Urine and Serum miRNA Signatures for the Non-Invasive Diagnosis of Adenomyosis: A Machine Learning-Based Pilot Study.","description":"<b>Background:</b> 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) profiles, combined with machine-learning approaches, could support non-invasive diagnosis. <b>Methods:</b> Serum and urine samples were collected from 59 patients undergoing surgery for chronic pelvic pain at the Endometriosis Centre of RWTH Aachen University Hospital. Seven patients had isolated adenomyosis, 34 had histologically confirmed endometriosis, and 18 served as negative controls. miRNAs were profiled using next-generation sequencing. A structured feature-selection pipeline (variance filtering, univariate testing, mutual information, rec","dates":{"release":"2025-01-01T00:00:00Z","publication":"2025 Nov","modification":"2026-05-26T11:09:00.256Z","creation":"2026-05-24T03:11:21.495Z"},"accession":"S-EPMC12691541","cross_references":{"pubmed":["41374393"],"doi":["10.3390/diagnostics15233012"]}}