Raman spectroscopy is an emerging technique in bioanalysis and imaging of biomaterials
owing to its unique capability of generating spectroscopic fingerprints. Imaging cells and …

Raman spectroscopy is used in a wide variety of fields, and in a plethora of different
configurations. Raman spectra of simple analytes can often be analyzed using univariate …

Abstract Machine learning has shown great potential for classifying diverse samples in
biomedical applications based on their Raman spectra. However, the acquired spectra …

Raman Spectra of Minerals | SpringerLink We’re sorry, something doesn't seem to be working
properly. Please try refreshing the page. If that doesn't work, please contact support so we can …

Surface-enhanced Raman scattering (SERS) imaging coupling with multivariate analysis in
spectral region of 200 to 1800 cm− 1 was developed to quantify and visualize thiophanate …

Objectives: To test whether mitochondrial transplantation (MITO) mitigates damage in 2
models of acute kidney injury (AKI). Background: MITO is a process where exogenous …

Machine learning has had a significant impact on the value of spectroscopic characterization
tools, particularly in biomedical applications, due to its ability to detect latent patterns within …

Raman spectroscopy, renowned for its unique ability to provide a molecular fingerprint, is an
invaluable tool in industry and academic research. However, various constraints often …

Bladder cancer (BCA) is relatively common and potentially recurrent/progressive disease. It
is also costly to detect, treat, and control. Definitive diagnosis is made by examination of …

A practical convolutional neural network (CNN) model is proposed to discriminate the
Raman spectra of human and animal blood. The proposed network, which discards the …