Andrology-Open Access
Open Access
ISSN: 2167-0250
ISSN: 2167-0250
Mengying Zhu, Xiaoquan Yang, Zhenzhu Zhai, Fang Chen, Ruibin Liu, Guohua Zhao and Yue Wang*
In recent years, the incidence of urological cancers, particularly Bladder Cancer (BC), Renal Cell Carcinoma (RCC) and Prostate Cancer (PCa), has significantly increased, highlighting the critical importance of early detection and timely treatment in improving patient outcomes. The often asymptomatic nature of these tumors in their early stages frequently leads to diagnoses at advanced stages, which adversely affects treatment efficacy and survival rates. The diagnosis of urological tumors relies on medical imaging, pathological slides and endoscopic images, all of which are essential for early detection but face limitations such as physician subjectivity and time-consuming analysis. The advent of Artificial Intelligence (AI) presents a promising solution for extracting features from tumor images that may be difficult to identify visually, thereby enhancing diagnostic accuracy. This is particularly advantageous in cases of poor imaging quality or when physicians have limited experience, as AI can provide more accurate pathological information. This article explores the vital role of AI in the early diagnosis of urological tumors, demonstrating how it assists physicians in identifying early signs through the analysis of medical images and data. By improving diagnostic accuracy and efficiency, AI not only enhances patient prognosis but also supports the development of personalized treatment plans, thus advancing the field of urology.
Published Date: 2025-10-20; Received Date: 2024-10-01