Shaping the Future of Personalized Therapy in Bladder Cancer Using Artificial Intelligence

Area of Science:

• Oncology
• Medical Informatics
• Artificial Intelligence

Background:

• Bladder cancer (BC) is a globally prevalent malignancy, posing significant challenges in patient care and clinical decision-making.
• Current BC management requires enhanced strategies for personalized treatment approaches.

Purpose of the Study:

• To provide an overview of artificial intelligence (AI) applications in various stages of bladder cancer management.
• To highlight AI's potential in developing individualized BC treatment strategies.
• To identify barriers hindering the widespread clinical adoption of AI in BC care.

Main Methods:

• Review of current artificial intelligence (AI) applications, including machine learning and deep learning, in bladder cancer (BC) workflows.
• Exploration of AI's role in BC detection, grading, staging, risk stratification, treatment selection, and outcome prediction.

Main Results:

• AI demonstrates potential for personalizing bladder cancer (BC) management across multiple clinical steps.
• Significant advancements in AI applications for BC are noted, with promising outcomes in various management areas.
• Key barriers remain that impede the broad integration of AI into routine BC clinical practice.

Conclusions:

• Artificial intelligence (AI) tools offer a promising avenue for personalized bladder cancer (BC) care.
• Overcoming existing obstacles is crucial for realizing the full potential of AI-driven BC management.
• Continued research and development are necessary before AI can be widely implemented in clinical settings for BC.