To summarize the applications of AI in the diagnosis and treatment of prostate cancer.
Approach:
Data Sources: Literature search was performed in PubMed and Web of Science for original research articles published between January 2022 and June 2023.
Key Findings:
AI-driven multi-modal models enhance diagnostic accuracy and efficiency in prostate cancer.
AI has been integrated into surgical procedures, radiation therapy, and targeted drug development.
Most AI models have not been practically implemented in clinical settings.
Interpretation:
AI has the potential to improve early detection, diagnosis, and personalized treatment of prostate cancer, but practical application remains limited.
Limitations:
Current AI technology has limitations in practical clinical use.
The review does not constitute a formal systematic review.
Conclusion:
AI's integration into prostate cancer management could alleviate workload for medical professionals and improve patient outcomes.
