AUTHOR=Zhu Mengying , Gu Zhichao , Chen Fang , Chen Xi , Wang Yue , Zhao Guohua TITLE=Application of artificial intelligence in the diagnosis and treatment of urinary tumors JOURNAL=Frontiers in Oncology VOLUME=14 YEAR=2024 URL=https://www.frontiersin.org/journals/oncology/articles/10.3389/fonc.2024.1440626 DOI=10.3389/fonc.2024.1440626 ISSN=2234-943X ABSTRACT=

Diagnosis and treatment of urological tumors, relying on auxiliary data such as medical imaging, while incorporating individual patient characteristics into treatment selection, has long been a key challenge in clinical medicine. Traditionally, clinicians used extensive experience for decision-making, but recent artificial intelligence (AI) advancements offer new solutions. Machine learning (ML) and deep learning (DL), notably convolutional neural networks (CNNs) in medical image recognition, enable precise tumor diagnosis and treatment. These technologies analyze complex medical image patterns, improving accuracy and efficiency. AI systems, by learning from vast datasets, reveal hidden features, offering reliable diagnostics and personalized treatment plans. Early detection is crucial for tumors like renal cell carcinoma (RCC), bladder cancer (BC), and Prostate Cancer (PCa). AI, coupled with data analysis, improves early detection and reduces misdiagnosis rates, enhancing treatment precision. AI’s application in urological tumors is a research focus, promising a vital role in urological surgery with improved patient outcomes. This paper examines ML, DL in urological tumors, and AI’s role in clinical decisions, providing insights for future AI applications in urological surgery.