Zhulin Bu

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About

Zhulin Bu is a pioneering researcher at the intersection of artificial intelligence and traditional medicine, with a primary focus on the standardization and modernization of Traditional Chinese Medicine (TCM) through machine learning and deep learning technologies. Their most cited work, "Progress in the application of AI in the standardization of traditional Chinese medicine: A review based on machine learning and deep learning" (2025, 10 citations), provides a comprehensive analysis of AI applications across six pivotal domains of TCM, including diagnostic pattern recognition, herbal formulation optimization, and quality control. This landmark review has been instrumental in charting a path toward an integrated and resilient healthcare future, bridging ancient medical wisdom with cutting-edge computational methods. Bu's contributions are particularly notable for demonstrating how AI can address long-standing challenges in TCM standardization, such as subjective diagnostic variability and complex herb-drug interactions. Their work has garnered attention from both the AI and integrative medicine communities, positioning Bu as a key figure in the Fourth Industrial Revolution's impact on healthcare. By systematically mapping the convergence of machine learning with traditional healing systems, Bu is helping to create evidence-based frameworks that could transform how TCM is practiced, taught, and regulated globally.