en Urology and Nephrology Urology and Nephrology Systematic Review <span style="font-size:13pt"><span style="text-justify:kashida"><span style="text-kashida:0%"><span style="text-autospace:none"><span style="font-family:&quot;Times New Roman&quot;,serif"><span style="font-style:italic"><b><span style="font-size:9.0pt"><span style="font-style:normal">Background: </span></span></b><span style="font-size:9.0pt"><span style="font-style:normal">Despite the rapid integration of artificial intelligence (AI) in urological practice, a comprehensive understanding of research evolution and impact patterns remains unexplored. This analysis provides a systematic examination of its scientific development and future potential.</span></span></span></span></span></span></span></span><br> <span style="font-size:13pt"><span style="text-justify:kashida"><span style="text-kashida:0%"><span style="text-autospace:none"><span style="font-family:&quot;Times New Roman&quot;,serif"><span style="font-style:italic"><span style="font-size:9.0pt"><span style="font-style:normal">&nbsp;&nbsp; <b>Methods:</b> We conducted a comprehensive analysis of AI-related urological publications through October 2024 using the Scopus database. The study incorporated English-language original articles and reviews, utilizing VOSviewer, GraphPad Prism, and Data Wrapper for analysis and visualization.</span></span></span></span></span></span></span></span><br> <span style="font-size:13pt"><span style="text-justify:kashida"><span style="text-kashida:0%"><span style="text-autospace:none"><span style="font-family:&quot;Times New Roman&quot;,serif"><span style="font-style:italic"><span style="font-size:9.0pt"><span style="font-style:normal">&nbsp;&nbsp; <b>Results: </b>Our investigation encompassed 5755 publications, comprising 5109 original articles and 646 reviews, with 63.9% being open access. The field demonstrated exponential growth from a single publication in 1971 to 1337 publications in 2024, garnering 112,583 citations. The past decade has witnessed the emergence of the most influential articles, particularly those focusing on deep learning (DL) applications in urological cancer detection. The USA-led global contributions (31.1%), followed by China (23.7%) and India (8.2%). &quot;Scientific Reports&quot; emerged as the leading journal with 171 publications. Titles and abstracts analysis revealed key focuses on DL in imaging (n = 1067), chronic kidney disease (n = 801), and advanced DL methodologies (n = 794). The keyword analysis identified &quot;machine learning&quot; as the dominant theme (1331 occurrences), with &quot;prostate cancer&quot; (955) and &quot;deep learning&quot; (838) following closely. Contemporary trends show significant shifts toward ChatGPT applications, pharmacovigilance, and AI-assisted surgical planning. In terms of international collaboration, the USA demonstrated the strongest network with a link strength of 1543.</span></span></span></span></span></span></span></span><br> <span style="font-size:13pt"><span style="text-justify:kashida"><span style="text-kashida:0%"><span style="text-autospace:none"><span style="font-family:&quot;Times New Roman&quot;,serif"><span style="font-style:italic"><b><span style="font-size:9.0pt"><span style="font-style:normal">&nbsp;&nbsp; Conclusion:</span></span></b><span style="font-size:9.0pt"><span style="font-style:normal"> This study traces AI&#39;s evolution in urology, from basic ML to advanced clinical tools, with particular advancement in radiomics, imaging, and biomarker analysis. Successful future implementation necessitates addressing ethical considerations, technical hurdles, and practical challenges while maintaining focus on patient safety and equitable healthcare access.</span></span></span></span></span></span></span></span><br> &nbsp; Artificial Intelligence, Machine Learning, Deep Learning, Urology, Prostate Cancer, Bladder Cancer, Trend Analysis, Bibliometric, Scientometric 1378 1396 http://mjiri.iums.ac.ir/browse.php?a_code=A-10-3673-8&slc_lang=en&sid=1 Kasra Hatampour drkasrahatampour@gmail.com 200319475328460095445 0009-0007-0767-0778 Yes Department of General Surgery, Loghman Medical Center, Shahid Beheshti University of Medical Sciences, Tehran, Iran Sina Baghi Keshtan Sinabk94@gmail.com 200319475328460095446 200319475328460095446 No Birjand University of Medical Sciences, Birjand, Iran Ghazal Mohammadi ghazalm14998@gmail.com 200319475328460095447 0009-0002-3003-6656 No Tehran University of Medical Sciences, Tehran, Iran Hassan Akbarniakhaky Hassan.akbarnia@yahoo.com 200319475328460095448 200319475328460095448 No Tehran University of Medical Sciences, Tehran, Iran Ali Faryabi Faryabi.ali@gmail.com 200319475328460095449 200319475328460095449 No Tehran University of Medical Sciences, Tehran, Iran Hossein Aazami Hossein.aazami@gmail.com 200319475328460095450 200319475328460095450 No Tehran University of Medical Sciences, Tehran, Iran Mohammad Reza Fattahi Mrfatahi93@gmail.com 200319475328460095451 200319475328460095451 No Student Research Committee, School of Advanced Technologies in Medicine, Shahid Beheshti University of Medical Sciences, Tehran, Iran Farhad Seif farhad.seif@outlook.com 200319475328460095452 200319475328460095452 No Department of Photodynamic, Medical Laser Research Center, Yara Institute, ACECR, Tehran, Iran Hojat Dehghanbanadaki dehghan.hojat@yahoo.com 200319475328460095453 200319475328460095453 No Tehran University of Medical Sciences, Tehran, Iran