Sahyun Pak, Sung Gon Park, Jeonghyun Park, Sung Tae Cho, Young Goo Lee, Hanjong Ahn
{"title":"人工智能在泌尿肿瘤学中的应用。","authors":"Sahyun Pak, Sung Gon Park, Jeonghyun Park, Sung Tae Cho, Young Goo Lee, Hanjong Ahn","doi":"10.4111/icu.20230435","DOIUrl":null,"url":null,"abstract":"<p><strong>Purpose: </strong>With the recent rising interest in artificial intelligence (AI) in medicine, many studies have explored the potential and usefulness of AI in urological diseases. This study aimed to comprehensively review recent applications of AI in urologic oncology.</p><p><strong>Materials and methods: </strong>We searched the PubMed-MEDLINE databases for articles in English on machine learning (ML) and deep learning (DL) models related to general surgery and prostate, bladder, and kidney cancer. The search terms were a combination of keywords, including both \"urology\" and \"artificial intelligence\" with one of the following: \"machine learning,\" \"deep learning,\" \"neural network,\" \"renal cell carcinoma,\" \"kidney cancer,\" \"urothelial carcinoma,\" \"bladder cancer,\" \"prostate cancer,\" and \"robotic surgery.\"</p><p><strong>Results: </strong>A total of 58 articles were included. The studies on prostate cancer were related to grade prediction, improved diagnosis, and predicting outcomes and recurrence. The studies on bladder cancer mainly used radiomics to identify aggressive tumors and predict treatment outcomes, recurrence, and survival rates. Most studies on the application of ML and DL in kidney cancer were focused on the differentiation of benign and malignant tumors as well as prediction of their grade and subtype. Most studies suggested that methods using AI may be better than or similar to existing traditional methods.</p><p><strong>Conclusions: </strong>AI technology is actively being investigated in the field of urological cancers as a tool for diagnosis, prediction of prognosis, and decision-making and is expected to be applied in additional clinical areas soon. Despite technological, legal, and ethical concerns, AI will change the landscape of urological cancer management.</p>","PeriodicalId":14522,"journal":{"name":"Investigative and Clinical Urology","volume":"65 3","pages":"202-216"},"PeriodicalIF":2.5000,"publicationDate":"2024-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11076794/pdf/","citationCount":"0","resultStr":"{\"title\":\"Applications of artificial intelligence in urologic oncology.\",\"authors\":\"Sahyun Pak, Sung Gon Park, Jeonghyun Park, Sung Tae Cho, Young Goo Lee, Hanjong Ahn\",\"doi\":\"10.4111/icu.20230435\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Purpose: </strong>With the recent rising interest in artificial intelligence (AI) in medicine, many studies have explored the potential and usefulness of AI in urological diseases. This study aimed to comprehensively review recent applications of AI in urologic oncology.</p><p><strong>Materials and methods: </strong>We searched the PubMed-MEDLINE databases for articles in English on machine learning (ML) and deep learning (DL) models related to general surgery and prostate, bladder, and kidney cancer. The search terms were a combination of keywords, including both \\\"urology\\\" and \\\"artificial intelligence\\\" with one of the following: \\\"machine learning,\\\" \\\"deep learning,\\\" \\\"neural network,\\\" \\\"renal cell carcinoma,\\\" \\\"kidney cancer,\\\" \\\"urothelial carcinoma,\\\" \\\"bladder cancer,\\\" \\\"prostate cancer,\\\" and \\\"robotic surgery.\\\"</p><p><strong>Results: </strong>A total of 58 articles were included. The studies on prostate cancer were related to grade prediction, improved diagnosis, and predicting outcomes and recurrence. The studies on bladder cancer mainly used radiomics to identify aggressive tumors and predict treatment outcomes, recurrence, and survival rates. Most studies on the application of ML and DL in kidney cancer were focused on the differentiation of benign and malignant tumors as well as prediction of their grade and subtype. Most studies suggested that methods using AI may be better than or similar to existing traditional methods.</p><p><strong>Conclusions: </strong>AI technology is actively being investigated in the field of urological cancers as a tool for diagnosis, prediction of prognosis, and decision-making and is expected to be applied in additional clinical areas soon. Despite technological, legal, and ethical concerns, AI will change the landscape of urological cancer management.</p>\",\"PeriodicalId\":14522,\"journal\":{\"name\":\"Investigative and Clinical Urology\",\"volume\":\"65 3\",\"pages\":\"202-216\"},\"PeriodicalIF\":2.5000,\"publicationDate\":\"2024-05-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11076794/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Investigative and Clinical Urology\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.4111/icu.20230435\",\"RegionNum\":3,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"UROLOGY & NEPHROLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Investigative and Clinical Urology","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.4111/icu.20230435","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"UROLOGY & NEPHROLOGY","Score":null,"Total":0}
Applications of artificial intelligence in urologic oncology.
Purpose: With the recent rising interest in artificial intelligence (AI) in medicine, many studies have explored the potential and usefulness of AI in urological diseases. This study aimed to comprehensively review recent applications of AI in urologic oncology.
Materials and methods: We searched the PubMed-MEDLINE databases for articles in English on machine learning (ML) and deep learning (DL) models related to general surgery and prostate, bladder, and kidney cancer. The search terms were a combination of keywords, including both "urology" and "artificial intelligence" with one of the following: "machine learning," "deep learning," "neural network," "renal cell carcinoma," "kidney cancer," "urothelial carcinoma," "bladder cancer," "prostate cancer," and "robotic surgery."
Results: A total of 58 articles were included. The studies on prostate cancer were related to grade prediction, improved diagnosis, and predicting outcomes and recurrence. The studies on bladder cancer mainly used radiomics to identify aggressive tumors and predict treatment outcomes, recurrence, and survival rates. Most studies on the application of ML and DL in kidney cancer were focused on the differentiation of benign and malignant tumors as well as prediction of their grade and subtype. Most studies suggested that methods using AI may be better than or similar to existing traditional methods.
Conclusions: AI technology is actively being investigated in the field of urological cancers as a tool for diagnosis, prediction of prognosis, and decision-making and is expected to be applied in additional clinical areas soon. Despite technological, legal, and ethical concerns, AI will change the landscape of urological cancer management.
期刊介绍:
Investigative and Clinical Urology (Investig Clin Urol, ICUrology) is an international, peer-reviewed, platinum open access journal published bimonthly. ICUrology aims to provide outstanding scientific and clinical research articles, that will advance knowledge and understanding of urological diseases and current therapeutic treatments. ICUrology publishes Original Articles, Rapid Communications, Review Articles, Special Articles, Innovations in Urology, Editorials, and Letters to the Editor, with a focus on the following areas of expertise:
• Precision Medicine in Urology
• Urological Oncology
• Robotics/Laparoscopy
• Endourology/Urolithiasis
• Lower Urinary Tract Dysfunction
• Female Urology
• Sexual Dysfunction/Infertility
• Infection/Inflammation
• Reconstruction/Transplantation
• Geriatric Urology
• Pediatric Urology
• Basic/Translational Research
One of the notable features of ICUrology is the application of multimedia platforms facilitating easy-to-access online video clips of newly developed surgical techniques from the journal''s website, by a QR (quick response) code located in the article, or via YouTube. ICUrology provides current and highly relevant knowledge to a broad audience at the cutting edge of urological research and clinical practice.