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Spectrum Analysis, Raman

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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...

Rapid diagnosis of membranous nephropathy based on serum and urine Raman spectroscopy combined with deep learning methods.

Scientific reports
Membranous nephropathy is the main cause of nephrotic syndrome, which has an insidious onset and may progress to end-stage renal disease with a high mortality rate, such as renal failure and uremia. At present, the diagnosis of membranous nephropathy...

Label-free detection of trace level zearalenone in corn oil by surface-enhanced Raman spectroscopy (SERS) coupled with deep learning models.

Food chemistry
Surface-enhanced Raman spectroscopy (SERS) and deep learning models were adopted for detecting zearalenone (ZEN) in corn oil. First, gold nanorods were synthesized as a SERS substrate. Second, the collected SERS spectra were augmented to improve the ...

Correlative Fluorescence and Raman Microscopy to Define Mitotic Stages at the Single-Cell Level: Opportunities and Limitations in the AI Era.

Biosensors
Nowadays, morphology and molecular analyses at the single-cell level have a fundamental role in understanding biology better. These methods are utilized for cell phenotyping and in-depth studies of cellular processes, such as mitosis. Fluorescence mi...

Industrial wastewater source tracing: The initiative of SERS spectral signature aided by a one-dimensional convolutional neural network.

Water research
The spectral fingerprint is a significant concept in nontarget screening of environmental samples to direct identification efforts to relevant and important features. Surface-enhanced Raman scattering (SERS) has long been recognized as an optical met...

Identification of Chinese red wine origins based on Raman spectroscopy and deep learning.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
In this study, we combined Raman spectroscopy with deep learning for the first time to establish an accurate, simple, and fast method to identify the origin of red wines. We collected Raman spectra from 200 red wine samples of the Cabernet Sauvignon ...

3D plasmonic coral nanoarchitecture paper for label-free human urine sensing and deep learning-assisted cancer screening.

Biosensors & bioelectronics
Practical human biofluid sensing requires a sensor device to differentiate patients from the normal group with high sensitivity and specificity. Label-free molecular identification from human biofluids allows direct classification of abnormal samples...

Classification of pathogenic bacteria by Raman spectroscopy combined with variational auto-encoder and deep learning.

Journal of biophotonics
Rapid and early identification of pathogens is critical to guide antibiotic therapy. Raman spectroscopy as a noninvasive diagnostic technique provides rapid and accurate detection of pathogens. Raman spectrum of single cells serves as the "fingerprin...

Rapid, label-free histopathological diagnosis of liver cancer based on Raman spectroscopy and deep learning.

Nature communications
Biopsy is the recommended standard for pathological diagnosis of liver carcinoma. However, this method usually requires sectioning and staining, and well-trained pathologists to interpret tissue images. Here, we utilize Raman spectroscopy to study hu...

Mid-level data fusion of Raman spectroscopy and laser-induced breakdown spectroscopy: Improving ores identification accuracy.

Analytica chimica acta
The identification of ore samples is of great scientific significance for mineral exploration, and geological evolution research on the planets. Attributed to the changes in the composition and structure of the same ore, the fusion of multiple techno...