{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,26]],"date-time":"2026-08-26T19:10:26Z","timestamp":1787771426145,"version":"build-2784847793"},"reference-count":17,"publisher":"MDPI AG","issue":"7","license":[{"start":{"date-parts":[[2026,3,26]],"date-time":"2026-03-26T00:00:00Z","timestamp":1774483200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["www.mdpi.com"],"crossmark-restriction":true},"short-container-title":["Diagnostics"],"abstract":"<jats:p>Background\/Objectives: Prostate cancer testing relies on prostate-specific antigen testing and digital rectal examination, which have limited specificity and face cultural or geographic barriers to access. We developed a non-invasive urine-based liquid biopsy assay using engineered hydrogel arrays and machine learning to detect disease-specific biochemical profiles. Methods: We collected voided urine samples from 283 participants at 26 U.S. urology practices prior to prostate biopsy. Random forest classifiers trained on 184 biopsy-confirmed cancer cases and 75 controls analyzed colorimetric signatures. Results: Across all Gleason grades (6\u201310), the assay achieved 97.8% sensitivity and 53.3% specificity. Performance varied by grade: high-grade cancers showed 97.3% specificity, while low-to-intermediate grades demonstrated 94.0% sensitivity. Conclusions: This accessible, culturally-appropriate platform could expand prostate cancer detection in diverse populations while reducing unnecessary invasive biopsies.<\/jats:p>","DOI":"10.3390\/diagnostics16070993","type":"journal-article","created":{"date-parts":[[2026,3,27]],"date-time":"2026-03-27T15:45:42Z","timestamp":1774626342000},"page":"993","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Urine-Based Machine Learning Assay Detects Prostate Cancer"],"prefix":"10.3390","volume":"16","author":[{"given":"Marvin S.","family":"Hausman","sequence":"first","affiliation":[{"name":"Genetics Institute of America, Delray Beach, FL 33445, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kyle","family":"Ambert","sequence":"additional","affiliation":[{"name":"PanGIA Biotech, Delray Beach, FL 33445, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Abhignyan","family":"Nagesetti","sequence":"additional","affiliation":[{"name":"PanGIA Biotech, Delray Beach, FL 33445, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Francis Buan Hong","family":"Lim","sequence":"additional","affiliation":[{"name":"PanGIA Biotech, Delray Beach, FL 33445, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Muthukarrupan","family":"Swaminathan","sequence":"additional","affiliation":[{"name":"PanGIA Biotech, Delray Beach, FL 33445, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0007-0402-739X","authenticated-orcid":false,"given":"Robert F.","family":"Cardwell","sequence":"additional","affiliation":[{"name":"Genetics Institute of America, Delray Beach, FL 33445, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Obdulio","family":"Piloto","sequence":"additional","affiliation":[{"name":"PanGIA Biotech, Delray Beach, FL 33445, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2026,3,26]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"63","DOI":"10.14740\/wjon1191","article-title":"Epidemiology of prostate cancer","volume":"10","author":"Rawla","year":"2019","journal-title":"World J. 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