AI Medical Compendium Journal:
Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy

Showing 41 to 50 of 184 articles

Fluorescence spectroscopy combined with multilayer perceptron deep learning to identify the authenticity of monofloral honey-Rape honey.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
Honey authenticity is critical to honey quality. The development of a quick, easy, and non-destructive technique for determining the authenticity of honey encourages an improvement in honey quality. Here, the authenticity of monofloral honey-rape hon...

Multimodal fish maw type recognition based on Wasserstein generative adversarial network combined with gradient penalty and spectral fusion.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
There are many types of fish maw with significantly varying prices. The specific type directly affects its market value and medicinal efficacy. This paper proposes a fish maw type recognition method based on Wasserstein generative adversarial network...

Plasma treated bimetallic nanofibers as sensitive SERS platform and deep learning model for detection and classification of antibiotics.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
Design of a sensitive, cost-effective SERS substrate is critical for probing analyte in trace concentration in real field environment. Present work reports the fabrication of an oxygen (O) plasma treated bimetallic nanofibers as a sensitive SERS plat...

Enhancing the accuracy of blood-glucose tests by upgrading FTIR with multiple-reflections, quantum cascade laser, two-dimensional correlation spectroscopy and machine learning.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
The accuracy of screening diabetes from non-diabetes is drastically enhanced by strategically upgrading the bench-marking infrared spectroscopy technique for non-invasive tests of blood-glucose, both with state-of-the-art instrumentation-retrofits an...

Simultaneous quantitative analysis of multiple metabolites using label-free surface-enhanced Raman spectroscopy and explainable deep learning.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
Metabolites serve as vital biomarkers, reflecting physiological and pathological states and offering insights into disease progression and early detection. This study introduces an advanced analytical technique integrating label-free Surface-Enhanced...

A new approach to assess post-mortem interval: A machine learning-assisted label-free ATR-FTIR analysis of human vitreous humor.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
A crucial issue in forensics is determining the post-mortem interval (PMI), the time between death and the finding of a body. Despite various methods already employed for its estimation, only approximate values are currently achievable. Vitreous humo...

Machine learning assisted rapid approach for quantitative prediction of biochemical parameters of blood serum with FTIR spectroscopy.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
This study develops regression models for predicting blood biochemical data using Fourier-transform infrared spectroscopy (FTIR) analysis. Absorption at specific wavelengths of blood serum is revealed to have strong correlations with biochemical para...

Enhanced cancer classification and critical feature visualization using Raman spectroscopy and convolutional neural networks.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
Cell misuse and cross-contamination pose a significant threat to the accuracy of cell research outcomes, often leading to the wasteful expenditure of time, manpower, and material resources. Consequently, the accurate identification of cell lines is p...

Molecular profiling of blood plasma-derived extracellular vesicles derived from Duchenne muscular dystrophy patients through integration of FTIR spectroscopy and machine learning reveals disease signatures.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
PURPOSE: To identify and monitor the FTIR spectral signatures of plasma extracellular vesicles (EVs) from Duchenne Muscular Dystrophy (DMD) patients at different stages with Healthy controls using machine learning models.

Siamese network for classification of Raman spectroscopy with inter-instrument variation for biological applications.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
Raman spectroscopy has emerged as a highly sensitive, rapid, and label-free detection method, extensively utilized in biological research. Presently, it is frequently paired with artificial intelligence (AI) algorithms to facilitate identification an...