AIMC Topic: Spectrum Analysis, Raman

Clear Filters Showing 61 to 70 of 526 articles

A novel approach to smart-assisted schizophrenia screening based on Raman spectroscopy and deep learning.

Scientific reports
In this study, serum Raman spectra are introduced into the screening of schizophrenia. We collect serum Raman spectra from schizophrenic and healthy individuals, classified them based on four convolutional neural networks, and developed an assisted s...

NAFLD progression in metabolic syndrome: a Raman spectroscopy and machine learning approach in an animal model.

The Analyst
Nonalcoholic fatty liver disease (NAFLD) is emerging as the leading cause of chronic liver disease in many regions, particularly in association with the rising prevalence of Metabolic syndrome (MetS), affecting more than 30% of the population worldwi...

Reflection-Enhanced Raman Identification of Single Bacterial Cells Patterned Using Capillary Assembly.

ACS sensors
Raman spectroscopy is an enticing tool for the rapid identification of pathogenic bacteria and has the potential to meet the demand for early diagnosis and timely treatment of patients. However, it remains a challenge to devise a reliable Raman detec...

Analysis of liquid biopsy by Raman spectroscopy to facilitate prediction of response to immunotherapy in non-small-cell lung cancer (NSCLC) patients.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
Immunotherapy has revolutionized lung cancer treatment, yet predicting patient response remains a challenge. This study used Raman spectroscopy to differentiate between non-small-cell lung cancer patients with short-lasting and long-lasting responses...

Machine learning-enhanced SERS detection of melamine and its analogues in non-pretreated milk via filter-pressing assembled polytetrafluoroethylene-AgNPs substrate.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
Melamine contamination from illegal additives, packaging contaminants, and pesticide residues threatens dairy product safety, demanding rapid detection. Traditional methods such as chromatography or mass spectrometry are precise but lack field applic...

Fast identification of influenza using label-free SERS combined with machine learning algorithms clinical nasal swab samples.

Analytical methods : advancing methods and applications
Influenza virus outbreaks, which have become more frequent in recent years, have attracted global attention. Reverse transcription-polymerase chain reaction (RT-PCR) and enzyme-linked immunosorbent assay (ELISA), as the "gold standard" methods for vi...

DiffRaman: A conditional latent denoising diffusion probabilistic model for enhancing bacterial identification via Raman spectra generation under limited data.

Analytica chimica acta
Raman spectroscopy has attracted significant attention in various biochemical detection fields, especially in the rapid identification of pathogenic bacteria. The integration of this technology with deep learning to facilitate automated bacterial Ram...

Wearable Double Network Plasmonic Hydrogel for SERS Detection of Urea and Uric Acid in Sweat.

ACS sensors
Traditional wearable devices for sweat detection often face limitations such as low detection sensitivity, insufficient mechanical properties, and discomfort during use. To address these challenges, hydrogels are utilized as sensor patches to improve...

Deep learning algorithm-assisted non-destructive detection of TBARS values of salmon flesh using multi-modal molecular spectra fusion.

Food chemistry
This study presents a deep learning framework for the non-destructive assessment of lipid oxidation in salmon flesh, quantified by thiobarbituric acid reactive substances (TBARS), under diverse storage conditions (-20, 0, 4, 20 °C, and dynamic temper...

Efficient wheat variety identification using Raman hyperspectral imaging in combination with deep learning.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
Wheat (Triticum aestivum L.) is recognized as a globally important staple crop, with its varietal differences influencing food processing, nutritional value, and agricultural productivity. Traditional identification methods are often considered ineff...