人工智能在泌尿肿瘤学中的应用。

IF 2.5 3区 医学 Q2 UROLOGY & NEPHROLOGY Investigative and Clinical Urology Pub Date : 2024-05-01 DOI:10.4111/icu.20230435
Sahyun Pak, Sung Gon Park, Jeonghyun Park, Sung Tae Cho, Young Goo Lee, Hanjong Ahn
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引用次数: 0

摘要

目的:随着近年来人工智能(AI)在医学中的应用日益受到关注,许多研究都探索了人工智能在泌尿系统疾病中的潜力和作用。本研究旨在全面回顾人工智能在泌尿肿瘤学中的最新应用:我们在 PubMed-MEDLINE 数据库中搜索了与普通外科以及前列腺癌、膀胱癌和肾癌相关的机器学习(ML)和深度学习(DL)模型的英文文章。检索词是关键词的组合,包括 "泌尿外科 "和 "人工智能 "以及以下关键词之一:"机器学习"、"深度学习"、"神经网络"、"肾细胞癌"、"肾癌"、"尿路上皮癌"、"膀胱癌"、"前列腺癌 "和 "机器人手术":共收录了 58 篇文章。有关前列腺癌的研究涉及分级预测、改善诊断、预测预后和复发。关于膀胱癌的研究主要利用放射组学来识别侵袭性肿瘤,预测治疗效果、复发率和生存率。大多数关于将 ML 和 DL 应用于肾癌的研究都集中在良性和恶性肿瘤的区分以及肿瘤分级和亚型的预测上。大多数研究表明,使用人工智能的方法可能优于或类似于现有的传统方法:人工智能技术作为诊断、预后预测和决策的工具,正在泌尿系统癌症领域积极开展研究,预计不久将应用于更多临床领域。尽管存在技术、法律和伦理方面的问题,但人工智能将改变泌尿系统癌症管理的格局。
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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.

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来源期刊
CiteScore
4.10
自引率
4.30%
发文量
82
审稿时长
4 weeks
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.
期刊最新文献
Analysis of sleep pattern in patients with nocturnal enuresis: A prospective, observational, pilot study. Application of deep learning for semantic segmentation in robotic prostatectomy: Comparison of convolutional neural networks and visual transformers. Association between soy products and prostate cancer: A systematic review and meta-analysis of observational studies. Dasatinib induces apoptosis and autophagy by suppressing the PI3K/Akt/mTOR pathway in bladder cancer cells. Multi-pharmacological treatment for young subfertile males with chronic prostatitis/chronic pelvic pain syndrome.
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