{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,2]],"date-time":"2026-03-02T22:45:00Z","timestamp":1772491500557,"version":"3.50.1"},"reference-count":34,"publisher":"MDPI AG","issue":"4","license":[{"start":{"date-parts":[[2023,9,27]],"date-time":"2023-09-27T00:00:00Z","timestamp":1695772800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"LSUHSC-School of Medicine Startup funds","award":["2U54GM104940-07"],"award-info":[{"award-number":["2U54GM104940-07"]}]},{"name":"LSUHSC-School of Medicine Startup funds","award":["2P20GM121288-06"],"award-info":[{"award-number":["2P20GM121288-06"]}]},{"name":"LSUHSC-School of Medicine Startup funds","award":["UL1TR003096"],"award-info":[{"award-number":["UL1TR003096"]}]},{"name":"National Institute of Health and National Institute of General Medical Sciences USA","award":["2U54GM104940-07"],"award-info":[{"award-number":["2U54GM104940-07"]}]},{"name":"National Institute of Health and National Institute of General Medical Sciences USA","award":["2P20GM121288-06"],"award-info":[{"award-number":["2P20GM121288-06"]}]},{"name":"National Institute of Health and National Institute of General Medical Sciences USA","award":["UL1TR003096"],"award-info":[{"award-number":["UL1TR003096"]}]},{"name":"National Center for Advancing Translational Sciences USA","award":["2U54GM104940-07"],"award-info":[{"award-number":["2U54GM104940-07"]}]},{"name":"National Center for Advancing Translational Sciences USA","award":["2P20GM121288-06"],"award-info":[{"award-number":["2P20GM121288-06"]}]},{"name":"National Center for Advancing Translational Sciences USA","award":["UL1TR003096"],"award-info":[{"award-number":["UL1TR003096"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["MAKE"],"abstract":"<jats:p>A critical unmet medical need in prostate cancer (PCa) clinical management centers around distinguishing indolent from aggressive tumors. Traditionally, Gleason grading has been utilized for this purpose. However, tumor classification using Gleason Grade 7 is often ambiguous, as the clinical behavior of these tumors follows a variable clinical course. This study aimed to investigate the application of machine learning techniques (ML) to classify patients into indolent and aggressive PCas. We used gene expression data from The Cancer Genome Atlas and compared gene expression levels between indolent and aggressive tumors to identify features for developing and validating a range of ML and stacking algorithms. ML algorithms accurately distinguished indolent from aggressive PCas. With the accuracy of 96%, the stacking model was superior to individual ML algorithms when all samples with primary Gleason Grades 6 to 10 were used. Excluding samples with Gleason Grade 7 improved accuracy to 97%. This study shows that ML algorithms and stacking models are powerful approaches for the accurate classification of indolent versus aggressive PCas. Future implementation of this methodology may significantly impact clinical decision making and patient outcomes in the clinical management of prostate cancer.<\/jats:p>","DOI":"10.3390\/make5040066","type":"journal-article","created":{"date-parts":[[2023,9,28]],"date-time":"2023-09-28T08:24:44Z","timestamp":1695889484000},"page":"1302-1319","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["PCa-Clf: A Classifier of Prostate Cancer Patients into Patients with Indolent and Aggressive Tumors Using Machine Learning"],"prefix":"10.3390","volume":"5","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-0868-5556","authenticated-orcid":false,"given":"Yashwanth Karthik Kumar","family":"Mamidi","sequence":"first","affiliation":[{"name":"Department of Computer Science, University of New Orleans, New Orleans, LA 70148, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9484-257X","authenticated-orcid":false,"given":"Tarun Karthik Kumar","family":"Mamidi","sequence":"additional","affiliation":[{"name":"Department of Genetics, Heersink School of Medicine, The University of Alabama at Birmingham, 720 20th Street S, Birmingham, AL 35294, USA"},{"name":"Center for Computational Genomics and Data Science, The University of Alabama at Birmingham, 912 18th Street S, Birmingham, AL 35233, USA"}]},{"given":"Md Wasi Ul","family":"Kabir","sequence":"additional","affiliation":[{"name":"Department of Computer Science, University of New Orleans, New Orleans, LA 70148, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9357-2977","authenticated-orcid":false,"given":"Jiande","family":"Wu","sequence":"additional","affiliation":[{"name":"Department of Genetics and the Bioinformatics and Genomics Program, Louisiana State University Health Sciences Center, School of Medicine, 533 Bolivar Street, New Orleans, LA 70112, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0110-2194","authenticated-orcid":false,"given":"Md Tamjidul","family":"Hoque","sequence":"additional","affiliation":[{"name":"Department of Computer Science, University of New Orleans, New Orleans, LA 70148, USA"}]},{"given":"Chindo","family":"Hicks","sequence":"additional","affiliation":[{"name":"Department of Genetics and the Bioinformatics and Genomics Program, Louisiana State University Health Sciences Center, School of Medicine, 533 Bolivar Street, New Orleans, LA 70112, USA"}]}],"member":"1968","published-online":{"date-parts":[[2023,9,27]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"1379","DOI":"10.1586\/14737140.2014.974565","article-title":"Key papers in prostate cancer","volume":"14","author":"Rodney","year":"2014","journal-title":"Expert Rev. 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