Lin Zhao, Xinglong Liu, Xiangying Deng
The integration of artificial intelligence (AI) and nanotechnology is reshaping cancer diagnosis and treatment. In this context, intelligent nanoplatforms are multifunctional nanoscale systems designed or optimized with the help of AI, capable of combining tumor sensing, targeted delivery, controlled release, and adaptive response within a single platform. AI can analyze large-scale multi-omics and clinical datasets to support early cancer detection, accurate diagnosis, prognosis assessment, and refinement of personalized treatment strategies, while nanotechnology enables precise tumor targeting and site-specific drug delivery through diverse nanocarriers, thereby reducing systemic toxicity and improving therapeutic efficacy. Their interaction allows more rational nanomedicine design by optimizing key properties such as targeting capability, stability, and responsiveness, and nano-enabled imaging and sensing provide high-resolution data that further enhance model performance. Together, these advances point toward more personalized and efficient strategies for cancer diagnosis, therapy, and monitoring, although challenges related to data sharing, standardization, privacy, ethics, regulation, and development costs still need to be addressed for broader and safer clinical implementation.