人工智能在良性前列腺增生中的应用现状。

IF 1 Q4 UROLOGY & NEPHROLOGY
Milap Shah, Nithesh Naik, Bm Zeeshan Hameed, Rahul Paul, Dasharathraj K Shetty, Sufyan Ibrahim, Bhavan Prasad Rai, Piotr Chlosta, Patrick Rice, Bhaskar K Somani
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引用次数: 0

摘要

应用人工智能预测良性前列腺增生微创治疗前的临床结果,解决了在流速、症状评分等多个评估参数下可靠性不足的问题。综述了各种人工智能模型及其在良性前列腺增生中的应用。检索策略适用于识别和审查人工智能应用方面的文献,包含以下关键词的专用搜索字符串:“机器学习”,“人工智能”和“良性前列腺增大”或“BPH”或“良性前列腺增生”。综述文章、编辑评论和非泌尿学研究被排除在外。在本综述中,来自4项研究的1600例患者,使用模糊系统、计算机视觉系统和临床数据挖掘等不同分类器,研究人工智能在良性前列腺增生诊断和严重程度预测中的应用,并确定导致治疗反应的临床因素。模糊系统诊断前列腺增生的正确率为90%,计算机视觉系统诊断前列腺增生的正确率为96.3%。数据挖掘在正确预测良性前列腺增生患者对药物治疗的临床反应方面的敏感性和特异性分别达到70%和50%。人工智能在泌尿外科领域越来越有吸引力,有可能改善诊断和病人护理。人工智能在前列腺增生中的应用前景广阔,但结果缺乏普遍性。然而,在未来,我们将看到临床模式的转变,因为人工智能应用将在指南中找到自己的位置,并彻底改变决策过程。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Current Applications of Artificial Intelligence in Benign Prostatic Hyperplasia.

Current Applications of Artificial Intelligence in Benign Prostatic Hyperplasia.

Current Applications of Artificial Intelligence in Benign Prostatic Hyperplasia.

Current Applications of Artificial Intelligence in Benign Prostatic Hyperplasia.

Artificial intelligence is used in predicting the clinical outcomes before minimally invasive treatments for benign prostatic hyperplasia, to address the insufficient reliability despite multiple assessment parameters, such as flow rates and symptom scores. Various models of artificial intelligence and its contemporary applications in benign prostatic hyperplasia are reviewed and discussed. A search strategy adapted to identify and review the literature on the application of artificial intelligence with a dedicated search string with the following keywords: "Machine Learning," "Artificial Intelligence," AND "Benign Prostate Enlargement" OR "BPH" OR "Benign Prostatic Hyperplasia" was included and categorized. Review articles, editorial comments, and non-urologic studies were excluded. In the present review, 1600 patients were included from 4 studies that used different classifiers such as fuzzy systems, computer-based vision systems, and clinical data mining to study the applications of artificial intelligence in diagnoses and severity prediction and determine clinical factors responsible for treatment response in benign prostatic hyperplasia. The accuracy to correctly diagnose benign prostatic hyperplasia by Fuzzy systems was 90%, while that of computer-based vision system was 96.3%. Data mining achieved sensitivity and specificity of 70% and 50%, respectively, in correctly predicting the clinical response to medical treatment in benign prostatic hyperplasia. Artificial intelligence is gaining attraction in urology, with the potential to improve diagnostics and patient care. The results of artificial intelligence-based applications in benign prostatic hyperplasia are promising but lack generalizability of results. However, in the future, we will see a shift in the clinical paradigm as artificial intelligence applications will find their place in the guidelines and revolutionize the decision-making process.

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来源期刊
Turkish journal of urology
Turkish journal of urology Medicine-Urology
CiteScore
2.10
自引率
0.00%
发文量
53
期刊介绍: The aim of the Turkish Journal of Urology is to contribute to the literature by publishing scientifically high-quality research articles as well as reviews, editorials, letters to the editor and case reports. The journal’s target audience includes, urology specialists, medical specialty fellows and other specialists and practitioners who are interested in the field of urology.
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