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This review details advances in AI for detecting and grading prostate cancer, predicting patient outcomes, and identifying molecular subtypes, proposing collaboration between AI systems and pathologists to reduce workload and improve treatment recommendations. It also outlines development processes, challenges, and summarizes public datasets and open-source code.",{"@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/harnessing-artificial-intelligence-for-prostate-cancer-management-review/336163/",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/harnessing-artificial-intelligence-for-prostate-cancer-management-review/336163.png","ImageObject",300,407,{"name":42,"@type":43},"Ava Thompson","Person",{"url":19,"name":45,"@type":46},"DocShare","Organization","application/pdf","2026-10-27","2026-09-21",true,{"@type":52,"interactionType":53,"userInteractionCount":55},"InteractionCounter",{"@type":54},"ViewAction",6,{"@type":57,"mainEntity":58},"FAQPage",[59,65,69],{"name":60,"@type":61,"acceptedAnswer":62},"How does the review describe traditional prostate cancer pathology review?","Question",{"text":63,"@type":64},"Traditional pathology review is crucial for decision-making but is labor intensive and subject to some level of subjectivity. Biopsy pathology and Gleason grade assignment play a central role in treatment planning.","Answer",{"name":66,"@type":61,"acceptedAnswer":67},"What capabilities of AI in prostate cancer pathology does the review highlight?",{"text":68,"@type":64},"The review highlights AI success in detecting and grading prostate cancer, predicting patient outcomes, and identifying molecular subtypes. It also frames AI as a way to support clinical collaboration with pathologists.",{"name":70,"@type":61,"acceptedAnswer":71},"What does the review propose regarding AI use in clinical practice?",{"text":72,"@type":64},"The review proposes AI-based methods could collaborate with pathologists to reduce workload and assist clinicians in formulating treatment recommendations. It also discusses the general process and challenges for developing AI pathology models.","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},336163,1790343486,{"code":4,"msg":82,"data":83},"success",[84,88,92,96,101,105,109,114,119,122,126],{"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":97,"doc_module":4,"doc_module_name":25,"category_name":98,"show_sort_weight":99,"slug":100},5,"Comic",60,"comic",{"id":55,"doc_module":4,"doc_module_name":25,"category_name":102,"show_sort_weight":103,"slug":104},"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":97,"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":139,"language":140,"language_code":8,"site_id":7,"html_lang":8,"table_of_contents":141,"faqs":142,"seo_title":143,"seo_description":12,"update_tm":144,"read_time":145},1649267921044,"https://us-avatar.wpscdn.com/avatar/1800007509477c92dfb?_k=1786009248482753345","ll  \nOPEN ACCESS  \nReview  \nHarnessing artificial intelligence for prostate cancer management  \nLingxuan Zhu,1,2,3,16 Jiahua Pan,1,16 Weiming Mou,4,16 Longxin Deng,5 Yinjie Zhu,1 Yanqing Wang,1 Gyan Pareek,6,7 Elias Hyams,6,7 Benedito A. Carneiro,8 Matthew J. Hadfield,8 Wafik S. El-Deiry,9 Tao Yang,10 Tao Tan,11 Tong Tong,12 Na Ta,13 Yan Zhu,13 Yisha Gao,13 Yancheng Lai,1,15 Liang Cheng,6,14,17,* Rui Chen,1,17,* and Wei Xue1,17,*  \n1Department of Urology, Renji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200127, China  \n2Department of Etiology and Carcinogenesis, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China  \n3Changping Laboratory, Beijing, China  \n4Department of Urology, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China  \n5Department of Urology, Shanghai Changhai Hospital, Second Military Medical University, Shanghai 200433, China  \n6Department of Surgery (Urology), Brown University Warren Alpert Medical School, Providence, RI, USA  \n7Minimally Invasive Urology Institute, Providence, RI, USA  \n8The Legorreta Cancer Center at Brown University, Lifespan Cancer Institute, Providence, RI, USA  \n9The Legorreta Cancer Center at Brown University, Laboratory of Translational Oncology and Experimental Cancer Therapeutics, Department of Pathology & Laboratory Medicine, The Warren Alpert Medical School of Brown University, The Joint Program in Cancer Biology, Brown University and Lifespan Health System, Division of Hematology/Oncology, The Warren Alpert Medical School of Brown University, Providence, RI, USA  \n10Department of Medical Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China  \n11 Faculty of Applied Sciences, Macao Polytechnic University, Address: [R. de](R. de) Lu´ıs Gonzaga Gomes, Macao, China  \n12College of Physics and Information Engineering, Fuzhou University, Fujian 350108, China  \n13Department of Pathology, Shanghai Changhai Hospital, Second Military Medical University, Shanghai 200433, China  \n14Department of Pathology and Laboratory Medicine, Department of Surgery (Urology), Brown University Warren Alpert Medical School, Lifespan Health, and the Legorreta Cancer Center at Brown University, Providence, RI, USA  \n15The First School of Clinical Medicine, Southern Medical University, Guangzhou, China  \n16These authors contributed equally  \n17Senior author  \n*Correspondence: [liang_cheng@yahoo.com](liang_cheng@yahoo.com) (L.C.), [drchenrui@foxmail.com](drchenrui@foxmail.com) (R.C.), [uroxuewei@163.com](uroxuewei@163.com) (W.X.) [https://doi.org/10.1016/j.xcrm.2024.101506](https://doi.org/10.1016/j.xcrm.2024.101506)  \nSUMMARY  \nProstate cancer (PCa) is a common malignancy in males. The pathology review of PCa is crucial for clinical decision-making, but traditional pathology review is labor intensive and subjective to some extent. Digital pathology and whole-slide imaging enable the application of artificial intelligence (AI) in pathology. This review highlights the success of AI in detecting and grading PCa, predicting patient outcomes, and identifying molecular subtypes. We propose that AI-based methods could collaborate with pathologists to reduce workload and assist clinicians in formulating treatment recommendations. We also introduce the general process and challenges in developing AI pathology models for PCa. Importantly, we summarize publicly available datasets and open-source codes to facilitate the utilization of existing data and the comparison of the performance of different models to improve future studies.  \nINTRODUCTION  \nProstate cancer (PCa) is the leading cause of cancer-related deaths in males, with an annual global incidence of approximately 1,414,259 new cases.1 Diagnosis typically involves co","cbCaigvuPLs07n10","https://ap.wps.com/l/cbCaigvuPLs07n10","pdf",2935643,17,"English","# Summary\n# Introduction\n## Clinical workflow and pathology assessment\n# AI applications in prostate cancer pathology\n## Detection and grading\n## Outcome prediction and molecular subtyping\n# AI development process and challenges\n## Model building and evaluation\n# Datasets and open-source codes\n## Public resources for comparison and reuse","[{\"question\":\"How does the review describe traditional prostate cancer pathology review?\",\"answer\":\"Traditional pathology review is crucial for decision-making but is labor intensive and subject to some level of subjectivity. Biopsy pathology and Gleason grade assignment play a central role in treatment planning.\"},{\"question\":\"What capabilities of AI in prostate cancer pathology does the review highlight?\",\"answer\":\"The review highlights AI success in detecting and grading prostate cancer, predicting patient outcomes, and identifying molecular subtypes. It also frames AI as a way to support clinical collaboration with pathologists.\"},{\"question\":\"What does the review propose regarding AI use in clinical practice?\",\"answer\":\"The review proposes AI-based methods could collaborate with pathologists to reduce workload and assist clinicians in formulating treatment recommendations. It also discusses the general process and challenges for developing AI pathology models.\"}]","Harnessing Artificial Intelligence for Prostate Cancer Management - Review | PDF",1790013938,43]