Pseudotargeted metabolomics-based random forest model for tracking plant species from herbal products-Reference-Cited by-同舟云学术

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Pseudotargeted metabolomics-based random forest model for tracking plant species from herbal products

Published:2023-09 Issue: Volume:118 Page:154927
ISSN:0944-7113
Container-title:Phytomedicine
language:en
Short-container-title:Phytomedicine

Author:

Cai Wen-Lu,Fang Can,Liu Li-Fang,Sun Fang-Yuan,Xin Gui-Zhong,Zheng Jia-Yi

Publisher

Elsevier BV

Subject

Complementary and alternative medicine,Drug Discovery,Pharmaceutical Science,Pharmacology,Molecular Medicine

Reference38 articles.

1. From quality markers to data mining and intelligence assessment: a smart quality-evaluation strategy for traditional Chinese medicine based on quality markers;Bai;Phytomedicine,2018

2. Random forests;Breiman;Mach. Learn.,2001

3. How to improve CHMs quality: enlighten from CHMs ecological cultivation;Cao;Chin. Herb. Med.,2021

4. Comparison of three officinal species of Callicarpa based on a biochemome profiling strategy with UHPLC-IT-MS and chemometrics analysis;Chen;J. Pharm. Biomed. Anal.,2017

5. Using random forest to detect multiple inherited metabolic diseases simultaneously based on GC–MS urinary metabolomics;Chen;Talanta,2021

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1. Hyperspectral Estimation of Chlorophyll Content in Grape Leaves Based on Fractional-Order Differentiation and Random Forest Algorithm;Remote Sensing;2024-06-15

2. Species discrimination of multiple botanical origins of Fritillaria species based on infrared spectroscopy, thin layer chromatography-image analysis and untargeted metabolomics;Phytomedicine;2024-01

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