AIMC Topic: Spectrum Analysis, Raman

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Biomedical Vibrational Spectroscopy in the Era of Artificial Intelligence.

Molecules (Basel, Switzerland)
Biomedical vibrational spectroscopy has come of age. The past twenty years have brought many advancements and new developments and now its practitioners face a new challenge: artificial intelligence. Artificial intelligence has the capability to dete...

On the estimation of sugars concentrations using Raman spectroscopy and artificial neural networks.

Food chemistry
In this paper, we present an analysis of the performance of Raman spectroscopy, combined with feed-forward neural networks (FFNN), for the estimation of concentration percentages of glucose, sucrose, and fructose in water solutions. Indeed, we analys...

A graphical user interface (NWUSA) for Raman spectral processing, analysis and feature recognition.

Journal of biophotonics
It is a practical necessity for non-professional users to interpret biologically derived Raman spectral information for obtaining accurate and reliable analytical results. An integrated Raman spectral analysis software (NWUSA) was developed for spect...

Raman spectroscopy combined with machine learning for rapid detection of food-borne pathogens at the single-cell level.

Talanta
Rapid detection of food-borne pathogens in early food contamination is a permanent topic to ensure food safety and prevent public health problems. Raman spectroscopy, a label-free, highly sensitive and dependable technology has attracted more and mor...

Potential of Raman spectroscopy in facilitating pharmaceutical formulations development - An AI perspective.

International journal of pharmaceutics
Drug development is time-consuming and inherently possesses a high failure rate. Pharmaceutical formulation development is the bridge that links a new chemical entity (NCE) to pre-clinical and clinical trials, and has a high impact on the efficacy an...

Raman spectroscopy of follicular fluid and plasma with machine-learning algorithms for polycystic ovary syndrome screening.

Molecular and cellular endocrinology
Polycystic ovary syndrome (PCOS) is the main cause of anovulatory infertility and affects women throughout their lives. The specific diagnostic method is still under investigation. In the present study, we aimed to identify the metabolic tracks of th...

Quantitative analysis of excipient dominated drug formulations by Raman spectroscopy combined with deep learning.

Analytical methods : advancing methods and applications
Owing to the growing interest in the application of Raman spectroscopy for quantitative purposes in solid pharmaceutical preparations, an article on the identification of compositions in excipient dominated drugs based on Raman spectra is presented. ...

Label-free SERS detection of proteins based on machine learning classification of chemo-structural determinants.

The Analyst
Establishing standardized methods for a consistent analysis of spectral data remains a largely underexplored aspect in surface-enhanced Raman spectroscopy (SERS), particularly applied to biological and biomedical research. Here we propose an effectiv...

Review of Laser Raman Spectroscopy for Surgical Breast Cancer Detection: Stochastic Backpropagation Neural Networks.

Sensors (Basel, Switzerland)
Laser Raman spectroscopy (LRS) is a highly specific biomolecular technique which has been shown to have the ability to distinguish malignant and normal breast tissue. This paper discusses significant advancements in the use of LRS in surgical breast ...

Machine Learning-Assisted Raman Spectroscopy for pH and Lactate Sensing in Body Fluids.

Analytical chemistry
This study presents the combination of Raman spectroscopy with machine learning algorithms as a prospective diagnostic tool capable of detecting and monitoring relevant variations of pH and lactate as recognized biomarkers of several pathologies. The...