AIMC Topic: Chromatography, High Pressure Liquid
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Promoting LC-QToF based non-targeted fingerprinting and biomarker selection with machine learning for the discrimination of black tea geographical origin.
Food chemistry
Nov 23, 2024
Traceability and mislabelling of black tea for their geographical origin is known as a major fraud concern of the sector. Discrimination among various geographical indications (GIs) can be challenging due to the complexity of chemical fingerprints in...
A Machine Learning-Based Approach for the Prediction of Anticoagulant Activity of Hypericum perforatum L. and Evaluation of Compound Activity.
Phytochemical analysis : PCA
Nov 17, 2024
INTRODUCTION: Hypericum perforatum L. (HPL) is extensively researched domestically and internationally as a medicinal plant. However, no reports of studies related to the anticoagulant activity of HPL have been retrieved. The specific bioactive compo...
Geographical classification of population: Analysis of amino acid in fingermark residues using UHPLC-QQQ-MS/MS combined with machine learning.
Forensic science international
Nov 8, 2024
OBJECTIVE: To determine the living regions of individuals based on amino acids in fingermark residues and to establish a rapid and accurate regional classification method using machine learning.
Development of deep learning software to improve HPLC and GC predictions using a new crown-ether based mesogenic stationary phase and beyond.
Journal of chromatography. A
Oct 28, 2024
The application of AI to analytical and separative sciences is a recent challenge that offers new perspectives in terms of data prediction. In this work, we report an AI-based software, named Chrompredict 1.0, which based on chromatographic data of a...
Untargeted Metabolomics and Soil Community Metagenomics Analyses Combined with Machine Learning Evaluation Uncover Geographic Differences in Ginseng from Different Locations.
Journal of agricultural and food chemistry
Sep 20, 2024
C.A. Meyer, known as the "King of Herbs," has been used as a nutritional supplement for both food and medicine with the functions of relieving fatigue and improving immunity for thousands of years in China. In agricultural planting, soil environment...
Optimization of the extraction process of total steroids from (Schwein.) Pat. by artificial neural network (ANN)-response surface methodology and identification of extract constituents.
Preparative biochemistry & biotechnology
Aug 23, 2024
(Schwein.) Pat has pharmacological effects such as tonifying the spleen, dispelling dampness, and strengthening the stomach, in which sterol is one of the main compounds of , but there has not been thought you to its extraction and detailed identifi...
Development of an equation to predict delta bilirubin levels using machine learning.
Clinica chimica acta; international journal of clinical chemistry
Aug 22, 2024
OBJECTIVE: Delta bilirubin (albumin-covalently bound bilirubin) may provide important clinical utility in identifying impaired hepatic excretion of conjugated bilirubin, but it cannot be measured in real-time for diagnostic purposes in clinical labor...
Fruit-In-Sight: A deep learning-based framework for secondary metabolite class prediction using fruit and leaf images.
PloS one
Aug 8, 2024
Fruits produce a wide variety of secondary metabolites of great economic value. Analytical measurement of the metabolites is tedious, time-consuming, and expensive. Additionally, metabolite concentrations vary greatly from tree to tree, making it dif...
Amino acid metabolomics and machine learning-driven assessment of future liver remnant growth after hepatectomy in livers of various backgrounds.
Journal of pharmaceutical and biomedical analysis
Jul 23, 2024
Accurate assessment of future liver remnant growth after partial hepatectomy (PH) in patients with different liver backgrounds is a pressing clinical issue. Amino acid (AA) metabolism plays a crucial role in liver regeneration. In this study, we comb...
Prediction of retention data of phenolic compounds by quantitative structure retention relationship models under reverse-phase liquid chromatography.
Journal of chromatography. A
Jul 9, 2024
Quantitative Structure-Retention Relationship models were developed to identify phenolic compounds using a typical LC- system, with both UV and MS detection. A new chromatographic method was developed for the separation of fifty-two standard phenolic...
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