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Updated: Aug 17, 2025

An Integrated Raman Spectroscopy and Mass Spectrometry Platform to Study Single-Cell Drug Uptake, Metabolism, and Effects
Published on: January 9, 2020
Study on the classification and identification of various carbonate and sulfate mineral medicines based on Raman
Siqingaowa Han1, Zhu Jin1, Dema Deji1
1Department of Combination of Mongolian Medicine and Western Medicine Stomatology, Affiliated Hospital of Inner Mongolia University for the Nationalities, Tongliao, 028043, China.
Abstract:
The efficacy of mineral medicines varies greatly between different origins. Therefore, investigating a method to quickly identify similar mineral medicines is meaningful. In this paper, a visual classification and identification model of Raman spectroscopy combined with principal component analysis (PCA) and support vector machine (SVM) algorithms was developed to rapidly classify and identify carbonate and sulfate mineral medicines. The results reveal that although the Raman spectra are too similar to distinguish by naked eye, the PCA-SVM algorithm can perform accurate classification and identification, and its accuracy, precision, recall and F1-score parameters all reach 100%. The proposed method is rapid, accurate, nondestructive, convenient, portable, and low cost, and has important application value for the classification, identification and quality supervision of various carbonate and sulfate mineral medicines.
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