AI Medical Compendium Journal:
Analytical and bioanalytical chemistry

Showing 21 to 30 of 42 articles

Unraveling surface-enhanced Raman spectroscopy results through chemometrics and machine learning: principles, progress, and trends.

Analytical and bioanalytical chemistry
Surface-enhanced Raman spectroscopy (SERS) has gained increasing attention because it provides rich chemical information and high sensitivity, being applicable in many scientific fields including medical diagnosis, forensic analysis, food control, an...

Machine learning toward high-performance electrochemical sensors.

Analytical and bioanalytical chemistry
The so-coined fourth paradigm in science has reached the sensing area, with the use of machine learning (ML) toward data-driven improvements in sensitivity, reproducibility, and accuracy, along with the determination of multiple targets from a single...

Machine learning-based protein crystal detection for monitoring of crystallization processes enabled with large-scale synthetic data sets of photorealistic images.

Analytical and bioanalytical chemistry
Since preparative chromatography is a sustainability challenge due to large amounts of consumables used in downstream processing of biomolecules, protein crystallization offers a promising alternative as a purification method. While the limited cryst...

A new dynamic deep learning noise elimination method for chip-based real-time PCR.

Analytical and bioanalytical chemistry
Point-of-care (POC) real-time polymerase chain reaction (PCR) has become one of the most important technologies for many fields such as pathogen detection and water-quality monitoring. POC real-time PCR usually adopts chips with small-volume chambers...

A photonic crystal fiber-based fluorescence sensor for simultaneous and sensitive detection of lactic acid enantiomers.

Analytical and bioanalytical chemistry
A photonic crystal fiber (PCF)-based fluorescence sensor is developed for rapid and sensitive detection of lactic acid (LA) enantiomers in serum samples. The sensor is fabricated by chemical binding dual enzymes on the inner surface of the PCF with n...

Rapid identification of the resistance of urinary tract pathogenic bacteria using deep learning-based spectroscopic analysis.

Analytical and bioanalytical chemistry
The resistance of urinary tract pathogenic bacteria to various antibiotics is increasing, which requires the rapid detection of infectious pathogens for accurate and timely antibiotic treatment. Here, we propose a rapid diagnosis strategy for the ant...

Discrimination of malignant from benign thyroid lesions through neural networks using FTIR signals obtained from tissues.

Analytical and bioanalytical chemistry
The current gold standard in cancer diagnosis-the microscopic examination of hematoxylin and eosin (H&E)-stained biopsies-is prone to bias since it greatly relies on visual examination. Hence, there is a need to develop a more sensitive and specific ...

SERS-based lateral flow assay combined with machine learning for highly sensitive quantitative analysis of Escherichia coli O157:H7.

Analytical and bioanalytical chemistry
In the present study, surface-enhanced Raman scattering-based lateral flow assay (SERS-LFA) strips were applied to promptly and sensitively detect Escherichia coli O157:H7 (E. coli O157:H7) to ensure food safety. The SERS nanotags were prepared by co...

Gas-phase volatilomic approaches for quality control of brewing hops based on simultaneous GC-MS-IMS and machine learning.

Analytical and bioanalytical chemistry
For the first time, a prototype HS-GC-MS-IMS dual-detection system is presented for the analysis of volatile organic compounds (VOCs) in fields of quality control of brewing hop. With a soft ionization and drift time-based ion separation in IMS and a...

A neural network approach for real-time particle/cell characterization in microfluidic impedance cytometry.

Analytical and bioanalytical chemistry
Microfluidic applications such as active particle sorting or selective enrichment require particle classification techniques that are capable of working in real time. In this paper, we explore the use of neural networks for fast label-free particle c...