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- W4378640117 endingPage "15" @default.
- W4378640117 startingPage "1" @default.
- W4378640117 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." @default.
- W4378640117 created "2023-05-30" @default.
- W4378640117 creator A5006578487 @default.
- W4378640117 creator A5023044882 @default.
- W4378640117 creator A5038655703 @default.
- W4378640117 creator A5052134746 @default.
- W4378640117 creator A5089277775 @default.
- W4378640117 date "2023-05-29" @default.
- W4378640117 modified "2023-10-16" @default.
- W4378640117 title "Applications of Hyperspectral Imaging Technology Combined with Machine Learning in Quality Control of Traditional Chinese Medicine from the Perspective of Artificial Intelligence: A Review" @default.
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- W4378640117 doi "https://doi.org/10.1080/10408347.2023.2207652" @default.
- W4378640117 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/37246728" @default.