The Current Status and Evaluation of Artificial Intelligence in Bladder Cancer: Clinical Applications and Research.
- 1School of Biomedical Sciences, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, China.
- 2Department of Urology, The Second Xiangya Hospital of Central South University, Hunan, China.
- 3School of Biomedical Engineering, The University of Hong Kong, Hong Kong SAR, China.
Abstract
Bladder cancer ranks as the 10th most common malignancy worldwide. Advances in technology are continuously reshaping its diagnosis, treatment selection, and prognosis assessment. In recent years, artificial intelligence (AI) has demonstrated marked potential in transforming bladder cancer care. By integrating and analyzing multi-source data, AI enhances the precision and efficiency of disease management. This review comprehensively examines the current applications of AI across various domains, including radiographic imaging analysis, pathological diagnosis, cystoscopic image processing, molecular subtyping, drug development, organoid research, prognostic modeling, and medical device innovation. It highlights the advantages of AI over conventional methods, outlines model development strategies, and summarizes commonly employed algorithms. Furthermore, we discuss the key challenges in translating AI tools into real-world clinical practice. This narrative review aims to inform the future development of AI-driven digital health systems, ultimately contributing to the realization of precision medicine and personalized management for bladder cancer patients.
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BibTeX
@article{yin2026current,
title = {{The Current Status and Evaluation of Artificial Intelligence in Bladder Cancer: Clinical Applications and Research.}},
author = {Zhuo Yin and Joshua W K Ho},
journal = {Computational and structural biotechnology journal},
year = {2026},
month = oct,
doi = {10.34133/csbj.0197},
url = {https://europepmc.org/article/MED/42898717},
note = {CC BY},
}
RIS
TY - JOUR
TI - The Current Status and Evaluation of Artificial Intelligence in Bladder Cancer: Clinical Applications and Research.
AU - Zhuo Yin
AU - Joshua W K Ho
PY - 2026
DA - 2026/10/19
JO - Computational and structural biotechnology journal
DO - 10.34133/csbj.0197
UR - https://europepmc.org/article/MED/42898717
AB - Bladder cancer ranks as the 10th most common malignancy worldwide. Advances in technology are continuously reshaping its diagnosis, treatment selection, and prognosis assessment. In recent years, artificial intelligence (AI) has demonstrated marked potential in transforming bladder cancer care. By integrating and analyzing multi-source data, AI enhances the precision and efficiency of disease management. This review comprehensively examines the current applications of AI across various domains, including radiographic imaging analysis, pathological diagnosis, cystoscopic image processing, molecular subtyping, drug development, organoid research, prognostic modeling, and medical device innovation. It highlights the advantages of AI over conventional methods, outlines model development strategies, and summarizes commonly employed algorithms. Furthermore, we discuss the key challenges in translating AI tools into real-world clinical practice. This narrative review aims to inform the future development of AI-driven digital health systems, ultimately contributing to the realization of precision medicine and personalized management for bladder cancer patients.
SN - 2001-0370
ER -