Peiran Song, Xuan Tang, Xukun Lv, Rui L. Reis, Xiao Chen, Long Bai, Jiacan Su
Abstract Artificial intelligence (AI) has emerged as a transformative force in biomedical engineering, catalyzing a shift toward data‐driven, intelligent research paradigms. With its advanced capabilities in computation, pattern recognition, and large‐scale data analysis, AI significantly enhances the efficiency, precision, and reproducibility of biomedical research. In particular, the convergence of AI with biomedical engineering has given rise to the emerging field of Digital Biomedical Engineering, which emphasizes the integration of AI technologies, big data analytics, and computational modeling to enable smart, predictive, and personalized solutions across life sciences. This review provides a comprehensive overview of the current landscape of AI applications in biomedical engineering, highlighting advances in medical image analysis, biosignal processing, biomaterials design, and drug development. It also emphasizes how AI improves diagnostic precision, accelerates material and drug discovery, and fosters personalized and predictive medicine. Additionally, it discusses the limitations and regulatory challenges of AI adoption, while outlining future directions to guide research innovation and clinical translation in the era of digital biomedicine.