Data-Driven Healing: Integrating Machine Learning with Traditional Chinese Medicinal Plants

Traditional Chinese Medicine (TCM) has long utilized medicinal plants for therapeutic purposes; however, scientific validation and standardization remain challenging due to their complex compositions and multi-target interactions. The integration of artificial intelligence (AI), particularly machine learning (ML) and deep learning (DL), has transformed herbal medicine research by enhancing the identification of medicinal plants, bioactive compound discovery, and pharmacological analysis. AI-powered approaches, including cheminformatics, network pharmacology, and spectral analysis, have streamlined quality control and prescription optimization processes. However, challenges such as data scarcity, a lack of standardized datasets, and the interpretability of AI-driven models hinder their widespread adoption. Addressing these limitations requires interdisciplinary collaboration, explainable AI models, and regulatory advancement. By bridging traditional wisdom with computational intelligence, AI can modernize TCM and improve its scientific credibility and integration into global healthcare.