Jingyi He, Luyuan Li, Shuhong Chen, Rong-Jun Chen, Jia-Le Zhuang, Chang Liu, Wesley Burrow, Jonghoon Chang, Tanziela Tanziela, R. Daniel Bonfil, Nai-Kei Wong, Wensi Tao
Management of metastatic prostate cancer (mPCa) poses significant challenges due to inherent tumor heterogeneity and therapeutic resistance. Advances in molecular imaging, liquid biopsies, and biomarkers are enabling precision oncology, while artificial intelligence (AI), including machine learning (ML) and deep learning (DL), integrates complex datasets to improve diagnostic accuracy, risk stratification, and treatment guidance. This review highlights AI's applications in mPCa, focusing on imaging, cell-free nucleic acids, circulating tumor cells, and genomic classifiers. We emphasize AI's role in enhancing diagnostics and personalizing treatments, with implications for improving clinical outcomes through better decision-making. Finally, we discuss opportunities and challenges in deploying AI systems, stressing multimodal integration and validation for real-world clinical impact.