Traditional Chinese Medicine (TCM) herbs are central to both prevention and treatment, yet their complex mechanisms remain only partly understood. This review examines how artificial intelligence (AI) has been applied to advance TCM herbal research, tracing its evolution from expert systems to machine learning, deep learning, and large language models. By analyzing both the traditional approach, rooted in classical TCM principles, and the modern approach, informed by biomedical science, we identify how AI enables knowledge extraction, prescription recommendation, compound discovery, and mechanism exploration. The review highlights the unique contribution of AI in bridging empirical heritage with scientific rigor, while also outlining key challenges such as data standardization and ethical considerations. Our findings demonstrate that the integration of AI with TCM herbs not only preserves traditional knowledge but also accelerates innovation in personalized and integrative medicine.
Wu et al. (2026) studied this question.