AI Medical Compendium Journal:
Journal of chromatography. A

Showing 11 to 20 of 66 articles

A holistic strategy for the in-depth discrimination and authentication of 16 citrus herbs and associated commercial products based on machine learning techniques and non-targeted metabolomics.

Journal of chromatography. A
Citrus-derived raw medicinal materials are frequently used for health care, flavoring, and therapeutic purposes. However, Due to similarities in origin or appearance, citrus herbs are often misused in the market, necessitating effective differentiati...

The application of design of experiments and artificial neural networks in the evaluation of the impact of acidic conditions on cloud point extraction.

Journal of chromatography. A
This study aimed to analyze the impact of acidic conditions on the recovery of ciprofloxacin and levofloxacin for cloud point extraction with the Design of Experiments and Artificial Neural Networks. The design included 27 experiments featuring three...

An unconventional separation method of α-Terpineol from its isomer 1,8-Cineole via in situ-association formation of deep eutectic solvent and machine learning.

Journal of chromatography. A
α-Terpineol and 1,8-cineole are two important compounds in essential oils. This study developed an efficient method to recover α-terpineol from model oil (MO) based on association extraction by in situ formations of deep eutectic solvent (DES) betwee...

Enhancing lipid identification in LC-HRMS data through machine learning-based retention time prediction.

Journal of chromatography. A
The comprehensive identification of peaks in untargeted lipidomics using LC-MS/MS remains a significant challenge. Confidence in lipid annotation can be greatly improved by integrating a highly accurate machine learning-based retention time predictio...

Implementation of machine learning tool for continued process verification of process chromatography unit operation.

Journal of chromatography. A
Recent advancements in technology, such as the emergence of artificial intelligence (AI) and machine learning (ML), have facilitated the progression of the biopharmaceutical industry toward the implementation of Industry 4.0. As per the guidelines se...

Developing physics-informed neural networks for model predictive control of periodic counter-current chromatography.

Journal of chromatography. A
The applications of continuous manufacturing technology in biopharmaceuticals require advanced design, monitoring, and control due to its complexity. Traditional mechanistic models, which rely on numerical solutions, suffer from long computational ti...

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
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...

Concept of flexible no-code automation for complex sample preparation procedures.

Journal of chromatography. A
Driven by demographic changes and dwindling Science Technology Engineering Mathematics enrolments, our research introduces no-code automation as a strategic response, aimed at mitigating labor shortages while enhancing productivity and safety in the ...

Discrimination of coal geographical origins through HS-GC-IMS assisted with machine learning algorithms in larceny case.

Journal of chromatography. A
The process of globalization and industrialization has resulted in a rise in the theft of coal and other related products, thereby becoming a focal point for forensic science. This situation has engendered an escalated demand for effective detection ...

Machine learning and matrix-assisted laser desorption/ionization time-of-flight mass spectra for antimicrobial resistance prediction: A systematic review of recent advancements and future development.

Journal of chromatography. A
BACKGROUND: The use of matrix-assisted laser desorption/ionization time-of-flight mass spectra (MALDI-TOF MS) combined with machine learning techniques has recently emerged as a method to address the public health crisis of antimicrobial resistance. ...