AI Medical Compendium Journal:
Journal of chromatography. A

Showing 41 to 50 of 66 articles

Retention time prediction in hydrophilic interaction liquid chromatography with graph neural network and transfer learning.

Journal of chromatography. A
The combination of retention time (RT), accurate mass and tandem mass spectra can improve the structural annotation in untargeted metabolomics. However, the incorporation of RT for metabolite identification has received less attention because of the ...

Hybrid Models for the simulation and prediction of chromatographic processes for protein capture.

Journal of chromatography. A
The biopharmaceutical industries are continuously faced with the pressure to reduce the development costs and accelerate development time scales. The traditional approach of heuristic-based or platform process-based optimization is soon getting obsol...

Automatic control of simulated moving bed process with deep Q-network.

Journal of chromatography. A
Optimal control of a simulated moving bed (SMB) process is challenging because the system dynamics is represented as nonlinear partial differential-algebraic equations combined with discrete events. In addition, product purity constraints are active ...

Transfer learning for small molecule retention predictions.

Journal of chromatography. A
Small molecule retention time prediction is a sophisticated task because of the wide variety of separation techniques resulting in fragmented data available for training machine learning models. Predictions are typically made with traditional machine...

Predicting Kováts Retention Indices Using Graph Neural Networks.

Journal of chromatography. A
The Kováts retention index is a dimensionless quantity that characterizes the rate at which a compound is processed through a gas chromatography column. This quantity is independent of many experimental variables and, as such, is considered a near-un...

Free amino acids in African indigenous vegetables: Analysis with improved hydrophilic interaction ultra-high performance liquid chromatography tandem mass spectrometry and interactive machine learning.

Journal of chromatography. A
A hydrophilic interaction (HILIC) ultra-high performance liquid chromatography (UHPLC) with triple quadrupole tandem mass spectrometry (MS/MS) method was developed and validated for the quantification of 21 free amino acids (AAs). Compared to publish...

Deep-Learning-Assisted multivariate curve resolution.

Journal of chromatography. A
Gas chromatography-mass spectrometry (GC-MS) is one of the major platforms for analyzing volatile compounds in complex samples. However, automatic and accurate extraction of qualitative and quantitative information is still challenging when analyzing...

Deep Learning on chromatographic data for Segmentation and Sensitive Analysis.

Journal of chromatography. A
Lateral flow immunoassay (LFIA) is one of the most common methods in point-of-care testing, which is widely applied in some conditions for various applications. Image segmentation is an increasingly popular experimental paradigm to efficiently test t...

Steroid identification via deep learning retention time predictions and two-dimensional gas chromatography-high resolution mass spectrometry.

Journal of chromatography. A
Untargeted steroid identification represents a great analytical challenge even when using sophisticated technology such as two-dimensional gas chromatography coupled to high resolution mass spectrometry (GC × GCHRMS) due to the chemical similarity of...

Enhancement of multianalyte mass spectrometry detection through response surface optimization by least squares and artificial neural network modelling.

Journal of chromatography. A
In this work, the use of design of experiments and posterior data modelling by artificial neural network (ANN) and least squares (LS) is presented as a suitable analytical tool for the performance optimization of a tandem mass spectrometric detector ...