AI Medical Compendium Topic

Explore the latest research on artificial intelligence and machine learning in medicine.

Chemometrics

Showing 1 to 10 of 17 articles

Clear Filters

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...

Spectrochemical analysis of blood combined with chemometric techniques for detecting osteosarcopenia.

Scientific reports
Among several complications related to physiotherapy, osteosarcopenia is one of the most frequent in elderly patients. This condition is limiting and quite harmful to the patient's health by disabling several basic musculoskeletal activities. Current...

NIR spectroscopy-CNN-enabled chemometrics for multianalyte monitoring in microbial fermentation.

Biotechnology and bioengineering
As the biopharmaceutical industry looks to implement Industry 4.0, the need for rapid and robust analytical characterization of analytes has become a pressing priority. Spectroscopic tools, like near-infrared (NIR) spectroscopy, are finding increasin...

Spectroscopy-based chemometrics combined machine learning modeling predicts cashew foliar macro- and micronutrients.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
Precision nutrient management in orchard crops needs precise, accurate, and real-time information on the plant's nutritional status. This is limited by the fact that it requires extensive leaf sampling and chemical analysis when it is to be done over...

Chemometrics methods, sensory evaluation and intelligent sensory technologies combined with GAN-based integrated deep-learning framework to discriminate salted goose breeds.

Food chemistry
The authenticity of salted goose products is concerning for consumers. This study describes an integrated deep-learning framework based on a generative adversarial network and combines it with data from headspace solid phase microextraction/gas chrom...

Production monitoring and quality characterization of black garlic using Vis-NIR hyperspectral imaging integrated with chemometrics strategies.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
As a new deep-processing garlic product with notable health benefits, the accurate discrimination of processing stages and prediction of key physicochemical constituents in black garlic are vital for maintaining product quality. This study proposed a...

Adulteration detection of multi-species vegetable oils in camellia oil using Raman spectroscopy: Comparison of chemometrics and deep learning methods.

Food chemistry
Oil adulteration is a global challenge in the production of high value-added natural oils. Raman spectroscopy combined with mathematical modeling can be used for adulteration detection of camellia oil (CAO). In this study, the advantages of tradition...

Combining stable isotopes and multi-elements with machine learning chemometric models to identify the geographical origins of Tetrastigma hemsleyanum Diels et Gilg.

Food chemistry
Tetrastigma hemsleyanum Diels et Gilg (T. hemsleyanum) is an edible plant with considerable medicinal properties, the quality of which varies depending on its origin. Therefore economically motivated adulteration has emerged. So there is an urgent ne...

A review: Integration of NIRS and chemometric methods for tea quality control-principles, spectral preprocessing methods, machine learning algorithms, research progress, and future directions.

Food research international (Ottawa, Ont.)
With the steady rise in tea production, the need for effective tea quality monitoring has become increasingly pressing. Traditional sensory evaluation and wet chemical detection methods are insufficient for real-time tea quality monitoring. As an eme...

Compressed chromatographic fingerprint of Artemisiae argyi Folium empowered by 1D-CNN: Reduce mobile phase consumption using chemometric algorithm.

Journal of chromatography. A
INTRODUCTION: High-Performance Liquid Chromatography (HPLC) is widely used for its high sensitivity, stability, and accuracy. Nonetheless, it often involves lengthy analysis times and considerable solvent consumption, especially when dealing with com...