Research Progress in AI-assisted Characteristic Pattern Analysis and Quality Evaluation Methods for Authentic Medicinal Materials

Abstract

Artificial intelligence technology is rapidly advancing, and research on the application of AI technology in the fields of quality identification and characteristic spectrum analysis of authentic medicinal materials is gaining increasing attention. Using deep learning, image recognition, chemical fingerprinting, and near-infrared spectroscopy, AI can efficiently and accurately analyze and evaluate the quality of traditional Chinese medicines. This review summarizes recent progress in the application of AI technology in the field of traditional Chinese medicine quality management, focusing on innovative applications of AI in areas such as medicinal material classification, fingerprint recognition, origin identification, and chemical composition analysis. AI technology has significantly improved the accuracy of medicinal material quality evaluation, implementing multidimensional fusion analysis of multi-source data , and enhancing the accuracy and efficiency of traditional Chinese medicine quality testing. Through the combination of artificial intelligence and data science, traditional Chinese medicine quality control has achieved a leap forward in standardization and automation, injecting new vitality into the modernization of traditional Chinese medicine. Drawing on recent literature research, this article summarizes the current status of AI application in the quality assessment of traditional Chinese herbal medicines, the challenges it faces, and future evolution trends.