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人工智能在良性前列腺增生中的当前应用

Current Applications of Artificial Intelligence in Benign Prostatic Hyperplasia.

作者信息

Shah Milap, Naik Nithesh, Hameed Bm Zeeshan, Paul Rahul, Shetty Dasharathraj K, Ibrahim Sufyan, Rai Bhavan Prasad, Chlosta Piotr, Rice Patrick, Somani Bhaskar K

机构信息

Robotics and Urooncology, Max Hospital and Max Institute of Cancer Care, New Delhi, India ; iTRUE (International Training and Research in Uro-oncology and Endourology) Group, Manipal, Karnataka, India.

iTRUE (International Training and Research in Uro-oncology and Endourology) Group, Manipal, Karnataka, India ; Department of Mechanical and Manufacturing Engineering, Manipal Institute of Technology, Manipal Academy of Higher Education, Manipal, Karnataka, India.

出版信息

Turk J Urol. 2022 Jul;48(4):262-267. doi: 10.5152/tud.2022.22028.

Abstract

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.

摘要

人工智能被用于预测良性前列腺增生微创治疗前的临床结果,以解决尽管有诸如流速和症状评分等多个评估参数,但可靠性仍不足的问题。本文综述并讨论了人工智能的各种模型及其在良性前列腺增生中的当代应用。采用一种搜索策略,通过一个专门的搜索字符串来识别和综述关于人工智能应用的文献,该字符串包含以下关键词:“机器学习”、“人工智能”以及“良性前列腺增生”或“BPH”或“良性前列腺肥大”,并对相关文献进行了分类。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,纳入了4项研究中的1600名患者,这些研究使用了不同的分类器,如模糊系统、基于计算机的视觉系统和临床数据挖掘,以研究人工智能在诊断和严重程度预测中的应用,并确定良性前列腺增生中影响治疗反应的临床因素。模糊系统正确诊断良性前列腺增生的准确率为90%,而基于计算机的视觉系统的准确率为96.3%。数据挖掘在正确预测良性前列腺增生药物治疗的临床反应方面,敏感性和特异性分别达到70%和50%。人工智能在泌尿外科越来越受到关注,具有改善诊断和患者护理的潜力。基于人工智能的良性前列腺增生应用结果很有前景,但缺乏结果的可推广性。然而,未来我们将看到临床范式的转变,因为人工智能应用将在指南中占据一席之地,并彻底改变决策过程。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1bdb/9612697/a5f7fae22c1f/tju-48-4-262_f001.jpg

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