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It also discusses implementation limitations and practical challenges, then evaluates how current models may enhance diagnostic accuracy, treatment planning, and patient outcomes, alongside the need for further validation.",{"@graph":14,"@context":73},[15,34,56],{"@type":16,"itemListElement":17},"BreadcrumbList",[18,23,27,31],{"item":19,"name":20,"@type":21,"position":22},"https://docshare.wps.com","Home","ListItem",1,{"item":24,"name":25,"@type":21,"position":26},"https://docshare.wps.com/document/","Document",2,{"item":28,"name":29,"@type":21,"position":30},"https://docshare.wps.com/document/healthcare/","Healthcare",3,{"item":32,"name":10,"@type":21,"position":33},"https://docshare.wps.com/document/exploring-the-use-of-artificial-intelligence-in-the-management-of-prostate-cancer/405522/",4,{"url":32,"name":10,"@type":35,"image":36,"author":41,"headline":10,"publisher":44,"fileFormat":47,"inLanguage":8,"description":12,"dateModified":48,"datePublished":49,"encodingFormat":47,"isAccessibleForFree":50,"interactionStatistic":51},"DigitalDocument",{"url":37,"@type":38,"width":39,"height":40},"https://docshare.wps.com/thumbnails/exploring-the-use-of-artificial-intelligence-in-the-management-of-prostate-cancer/405522.png","ImageObject",300,407,{"name":42,"@type":43},"Emma Wilson","Person",{"url":19,"name":45,"@type":46},"DocShare","Organization","application/pdf","2026-10-26","2026-09-28",true,{"@type":52,"interactionType":53,"userInteractionCount":55},"InteractionCounter",{"@type":54},"ViewAction",5,{"@type":57,"mainEntity":58},"FAQPage",[59,65,69],{"name":60,"@type":61,"acceptedAnswer":62},"What is the review’s purpose regarding AI in prostate cancer management?","Question",{"text":63,"@type":64},"The review explores the current state of research on AI use in prostate cancer management and examines applications such as image analysis, prediction of treatment outcomes, and patient stratification. It also evaluates limitations and challenges for implementation.","Answer",{"name":66,"@type":61,"acceptedAnswer":67},"What areas of prostate cancer diagnostics have recent AI focus?",{"text":68,"@type":64},"Recent literature highlighted in the review focuses on AI in radiomics and pathomics, as well as evaluation of surgical skills and patient outcomes. In the diagnostics section, radiomics and Gleason score prediction are emphasized.",{"name":70,"@type":61,"acceptedAnswer":71},"How does radiomics contribute to AI-driven prostate cancer insights?",{"text":72,"@type":64},"Radiomics extracts quantitative features from medical imaging such as CT and MRI. AI models can use these features to identify tumor characteristics like size, shape, texture, and intensity, supporting objective, data-driven monitoring and outcome prediction.","https://schema.org",{"og:url":32,"og:type":75,"og:title":10,"og:site_name":45,"og:description":12},"article",{"robots":77,"canonical":32},"index,follow",{"doc_id":79,"site_id":7},405522,1791120939,{"code":4,"msg":82,"data":83},"success",[84,88,92,96,100,105,109,114,119,122,126],{"id":22,"doc_module":4,"doc_module_name":25,"category_name":85,"show_sort_weight":86,"slug":87},"Story & Novel",90,"story-novel",{"id":26,"doc_module":4,"doc_module_name":25,"category_name":89,"show_sort_weight":90,"slug":91},"Literature",80,"literature",{"id":33,"doc_module":4,"doc_module_name":25,"category_name":93,"show_sort_weight":94,"slug":95},"Exam",70,"exam",{"id":55,"doc_module":4,"doc_module_name":25,"category_name":97,"show_sort_weight":98,"slug":99},"Comic",60,"comic",{"id":101,"doc_module":4,"doc_module_name":25,"category_name":102,"show_sort_weight":103,"slug":104},6,"Technology",50,"technology",{"id":106,"doc_module":4,"doc_module_name":25,"category_name":29,"show_sort_weight":107,"slug":108},7,40,"healthcare",{"id":110,"doc_module":4,"doc_module_name":25,"category_name":111,"show_sort_weight":112,"slug":113},8,"Research & Report",30,"research-report",{"id":115,"doc_module":4,"doc_module_name":25,"category_name":116,"show_sort_weight":117,"slug":118},9,"Religion & Spirituality",20,"religion-spirituality",{"id":117,"doc_module":4,"doc_module_name":25,"category_name":120,"show_sort_weight":117,"slug":121},"World Cup","world-cup",{"id":123,"doc_module":4,"doc_module_name":25,"category_name":124,"show_sort_weight":123,"slug":125},10,"Lifestyle","lifestyle",{"id":127,"doc_module":4,"doc_module_name":25,"category_name":128,"show_sort_weight":55,"slug":129},19,"General","general",{"code":4,"msg":82,"data":131},{"doc_id":79,"user_id":132,"nickname":42,"user_avatar":133,"doc_module":4,"category_id":106,"category_name":29,"doc_title":10,"doc_description":12,"doc_content":134,"file_id":135,"file_url":136,"file_type":137,"file_size":138,"view_count":55,"is_deleted":4,"is_public":22,"is_downloadable":22,"audit_status":22,"page_count":123,"language":139,"language_code":8,"site_id":7,"html_lang":8,"table_of_contents":140,"faqs":141,"seo_title":142,"seo_description":12,"update_tm":143,"read_time":144,"preview_page_count":4},3848291630094,"https://eur-avatar.wpscdn.com/davatar_085a072bc5b1113ac321206ff7593b45","Current Urology Reports (2023) 24:231–240  \n[https://doi.org/10.1007/s1](https://doi.org/10.1007/s1) 1934-023-01149-6  \nExploring the Use of Artificial Intelligence in the Management of Prostate Cancer  \nTimothy N. Chu1 · ElyssaY. Wong1 · Runzhuo Ma1 · Cherine H. Yang1 · Istabraq S. Dalieh1 · Andrew J. Hung1  \nAccepted: 30 January 2023 / Published online: 18 February 2023 © The Author(s) 2023  \nAbstract  \nPurpose of Review This review aims to explore the current state of research on the use of artificial intelligence (AI) in the management of prostate cancer. We examine the various applications of AI in prostate cancer, including image analysis, prediction of treatment outcomes, and patient stratification. Additionally, the review will evaluate the current limitations and challenges faced in the implementation of AI in prostate cancer management.  \nRecent Findings Recent literature has focused particularly on the use of AI in radiomics, pathomics, the evaluation of surgical skills, and patient outcomes.  \nSummary AI has the potential to revolutionize the future of prostate cancer management by improving diagnostic accuracy, treatment planning, and patient outcomes. Studies have shown improved accuracy and efficiency of AI models in the detection and treatment of prostate cancer, but further research is needed to understand its full potential as well as limitations.  \nKeywords Artificial intelligence · Machine learning · Prostate cancer · Radiomics · Pathomics  \nIntroduction  \nArtificial intelligence (AI) and machine learning (ML) are rapidly advancing fields that have the potential to revolutionize many industries, including medicine. AI involves the development of intelligent systems to perform tasks that typically require human intelligence, such as recognizing patterns and making decisions. AI performance is driven by ML, which harnesses algorithms and statistical models to automatically improve system performance on a specific task through experience. Over the last decade, AI has started to become increasingly integrated into medicine. Specifically, in the field of urology, AI is being tested and implemented as a tool to aid in the diagnosis and treatment of prostate cancer. AI-driven techniques are highly appealing because they can quickly analyze large amounts of data, such  \nThis article is part of the Topical Collection on Prostate Cancer  \n* Andrew J. Hung [andrew.hung@med.usc.edu](andrew.hung@med.usc.edu)  \n1 Center for Robotic Simulation & Education, Department of Urology, USC Institute of Urology, University of Southern California, Catherine & Joseph Aresty1441 Eastlake Avenue Suite 7416, Los Angeles, CA 90089, USA  \nas medical images and tissue samples, to identify patterns and make predictions about the likelihood of cancer [1] . In addition, AI-based techniques show the potential to increase the accuracy of prostate cancer diagnosis and improve treatment plans for patients. In this review, we explore recent AI advances in the diagnosis, prognosis, and treatment of localized prostate cancer. We share key studies and the impact they bring to each of these areas and highlight potential avenues for future research.  \nMethods  \nA comprehensive review of the current literature was performed using the PubMed-Medline database up to 2023 using the term “urology” combined with the following terms: “prostate cancer” and “artificial intelligence.” To capture recent trends in ML and DL applications, our search was focused on articles published within the last 4 years and originally published in English. Review articles and editorials were excluded. Publications relevant to the subject and their cited references were retrieved and appraised independently by 2 authors for inclusion in the final manuscript.  \nDiagnostics  \nRadiomics  \nAnalysis of cross-sectional radiographic images, like those produced by CT scans or MRI, is used to identify complex patterns, a task that AI can be trained to perform quickly, accurately, and con","cbCaip1XzljvaO2D","https://ap.wps.com/l/cbCaip1XzljvaO2D","pdf",743811,"English","# Abstract\n## Purpose of Review\n## Recent Findings\n## Summary\n# Introduction\n# Methods\n## Literature search approach\n# Diagnostics\n## Radiomics\n## Radiomics and Gleason Score","[{\"question\":\"What is the review’s purpose regarding AI in prostate cancer management?\",\"answer\":\"The review explores the current state of research on AI use in prostate cancer management and examines applications such as image analysis, prediction of treatment outcomes, and patient stratification. It also evaluates limitations and challenges for implementation.\"},{\"question\":\"What areas of prostate cancer diagnostics have recent AI focus?\",\"answer\":\"Recent literature highlighted in the review focuses on AI in radiomics and pathomics, as well as evaluation of surgical skills and patient outcomes. In the diagnostics section, radiomics and Gleason score prediction are emphasized.\"},{\"question\":\"How does radiomics contribute to AI-driven prostate cancer insights?\",\"answer\":\"Radiomics extracts quantitative features from medical imaging such as CT and MRI. AI models can use these features to identify tumor characteristics like size, shape, texture, and intensity, supporting objective, data-driven monitoring and outcome prediction.\"}]","Exploring the Use of Artificial Intelligence in the Management of Prostate Cancer | PDF",1790560397,25]