Abstract: The artificial intelligence (AI) -based healthcare system, by integrating multi-phase temporal data, multi-modal imaging features, and multidimensional bioinformatics parameters, demonstrates great potential to continuously optimize existing clinical practice paradigms and drive systemic transformations in healthcare. This study systematically elaborates on AI technologies and the framework for constructing AI healthcare models based on large-scale clinical data, subsequently presenting a research pathway that improves model performance through a closed-loop data iteration mechanism. Furthermore, a detailed roadmap for the development of AIbased healthcare is provided. In particular, this study takes prostate cancer as an example to showcase the future applications of AI in healthcare, illustrating the implementation pathways of AI technologies in disease screening, diagnostic decision-making, and prognosis assessment. Based on the aforementioned research, the"Digital Human"concept model for smart healthcare is innovatively proposed. This model, by integrating dynamic biological feature data and electronic health records, provides a theoretical framework for personalized health management. It is believed that the continuously evolving AI technologies will fundamentally reshape the future healthcare ecosystem by reconstructing diagnostic and treatment processes, optimizing resource allocation, and innovating service models.