Applications of Hyperspectral Imaging Technology Combined with Machine Learning in Quality Control of Traditional Chinese Medicine from the Perspective of Artificial Intelligence: A Review.
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引用次数: 0
Abstract
Traditional Chinese medicine (TCM) is the treasure of China, and the quality control of TCM is of crucial importance. In recent years, with the quick rise of artificial intelligence (AI) and the rapid development of hyperspectral imaging (HSI) technology, the combination of the two has been widely used in the quality evaluation of TCM. Machine learning (ML) is the core wisdom of AI, and its progress in rapid analysis and higher accuracy improves the potential of applying HSI to the field of TCM. This article reviewed five aspects of ML applied to hyperspectral data analysis of TCM: partition of data set, data preprocessing, data dimension reduction, qualitative or quantitative models, and model performance measurement. The different algorithms proposed by researchers for quality assessment of TCM were also compared. Finally, the challenges in the analysis of hyperspectral images for TCM were summarized, and the future works were prospected.
期刊介绍:
Critical Reviews in Analytical Chemistry continues to be a dependable resource for both the expert and the student by providing in-depth, scholarly, insightful reviews of important topics within the discipline of analytical chemistry and related measurement sciences. The journal exclusively publishes review articles that illuminate the underlying science, that evaluate the field''s status by putting recent developments into proper perspective and context, and that speculate on possible future developments. A limited number of articles are of a "tutorial" format written by experts for scientists seeking introduction or clarification in a new area.
This journal serves as a forum for linking various underlying components in broad and interdisciplinary means, while maintaining balance between applied and fundamental research. Topics we are interested in receiving reviews on are the following:
· chemical analysis;
· instrumentation;
· chemometrics;
· analytical biochemistry;
· medicinal analysis;
· forensics;
· environmental sciences;
· applied physics;
· and material science.