Will artificial intelligence (AI) replace cytopathologists: a scoping review of current applications and evidence of A.I. in urine cytology.

IF 2.8 2区 医学 Q2 UROLOGY & NEPHROLOGY
Jingqiu Li, Tsung Wen Chong, Khi Yung Fong, Benjamin Lim Jia Han, Si Ying Tan, Joanne Tan San Mui, Li Yan Khor, Bhaskar Kumar Somoni, Thomas R W Herrmann, Vineet Gauhar, Valerie Gan Huei Li, Christopher Cheng Wai Sam, Ee Jean Lim
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Abstract

Purpose: Urine cytology, while valuable in facilitating the detection and surveillance of bladder cancer, has notable limitations. The application of artificial intelligence (AI) in urine cytology holds significant promise for improving diagnostic accuracy and efficiency. Our scoping review aims to assess the current evidence of AI's utility in urine cytology.

Method: An electronic literature research on the application of AI in the setting of urine cytology was conducted on PubMed, EMBASE, and Scopus from inception to 1st November 2024. Case reports, abstracts, and reviews were excluded from this analysis. Our search strategy retrieved 1356 articles; after excluding 142 duplicates, the remaining 1214 papers were screened by title and abstract. 31 studies entered full-article review, and a total of 16 articles were included in the final analysis.

Results: The main application of AI in urine cytology diagnosis is to automate the identification and characterization of abnormal cells. It has also been utilized for risk stratification of abnormal cells, predicting histologic results from urine cytology samples, and predicting bladder cancer recurrence. Current limitation includes the need for robust training datasets and validation studies to ensure the generalizability of AI algorithms.

Conclusion: In summary, AI in urine cytology, though still developing, shows significant promise in enhancing diagnostic accuracy and efficiency. Current evidence suggests that AI, as a valuable tool, could revolutionize urinary tract cancer diagnosis and management.

人工智能(AI)将取代细胞病理学家:对人工智能在尿液细胞学中的当前应用和证据的范围审查。
目的:尿细胞学检查对膀胱癌的发现和监测有重要价值,但也有明显的局限性。人工智能(AI)在尿液细胞学中的应用对提高诊断准确性和效率具有重要的前景。我们的范围综述旨在评估人工智能在尿细胞学中的应用的现有证据。方法:在PubMed、EMBASE和Scopus数据库中对人工智能在尿液细胞学设置中的应用进行电子文献研究,研究时间为成立之日至2024年11月1日。病例报告、摘要和综述被排除在本分析之外。我们的搜索策略检索了1356篇文章;排除142篇重复后,按题目和摘要筛选剩余1214篇论文。31项研究进入全文综述,共有16篇文章被纳入最终分析。结果:人工智能在尿液细胞学诊断中的主要应用是对异常细胞的自动识别和表征。它也被用于异常细胞的风险分层,预测尿液细胞学样本的组织学结果,预测膀胱癌复发。目前的限制包括需要稳健的训练数据集和验证研究,以确保人工智能算法的可泛化性。结论:尿液细胞学中的人工智能虽然仍在发展中,但在提高诊断准确性和效率方面具有重要的前景。目前的证据表明,人工智能作为一种有价值的工具,可以彻底改变尿路癌的诊断和治疗。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
World Journal of Urology
World Journal of Urology 医学-泌尿学与肾脏学
CiteScore
6.80
自引率
8.80%
发文量
317
审稿时长
4-8 weeks
期刊介绍: The WORLD JOURNAL OF UROLOGY conveys regularly the essential results of urological research and their practical and clinical relevance to a broad audience of urologists in research and clinical practice. In order to guarantee a balanced program, articles are published to reflect the developments in all fields of urology on an internationally advanced level. Each issue treats a main topic in review articles of invited international experts. Free papers are unrelated articles to the main topic.
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