AIMC Topic: Spectrum Analysis, Raman

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A machine-learning approach to calibrate generic Raman models for real-time monitoring of cell culture processes.

Biotechnology and bioengineering
The manufacture of biotherapeutic proteins consists of complex upstream unit operations requiring multiple raw materials, analytical techniques, and control strategies to produce safe and consistent products for patients. Raman spectroscopy is a ubiq...

Optical screening of hepatitis-B infected blood sera using optical technique and neural network classifier.

Photodiagnosis and photodynamic therapy
In this study we demonstrate the analysis of biochemical changes in the human blood sera infected with Hepatitis B virus (HBV) using Raman spectroscopy. In total, 120 diseased blood samples and 170 healthy blood samples, collected from Pakistan Atomi...

Raman spectroscopic histology using machine learning for nonalcoholic fatty liver disease.

FEBS letters
Histopathology requires the expertise of specialists to diagnose morphological features of cells and tissues. Raman imaging can provide additional biochemical information to benefit histological disease diagnosis. Using a dietary model of nonalcoholi...

Data fusion strategies for performance improvement of a Process Analytical Technology platform consisting of four instruments: An electrospinning case study.

International journal of pharmaceutics
The aim of this work was to develop a PAT platform consisting of four complementary instruments for the characterization of electrospun amorphous solid dispersions with meloxicam. The investigated methods, namely NIR spectroscopy, Raman spectroscopy,...

Application of artificial neural networks for Process Analytical Technology-based dissolution testing.

International journal of pharmaceutics
This work proposes the application of artificial neural networks (ANN) to non-destructively predict the in vitro dissolution of pharmaceutical tablets from Process Analytical Technology (PAT) data. An extended release tablet formulation was studied, ...

Diagnosis of cervical squamous cell carcinoma and cervical adenocarcinoma based on Raman spectroscopy and support vector machine.

Photodiagnosis and photodynamic therapy
In this report, we collected the Raman spectrum of cervical adenocarcinoma and cervical squamous cell carcinoma tissues by a micro-Raman spectroscopy system. We analysed, compared and summarized the characteristics and differences of the normalized m...

Speeding Up the Line-Scan Raman Imaging of Living Cells by Deep Convolutional Neural Network.

Analytical chemistry
Raman imaging is a promising technique that allows the spatial distribution of different components in the sample to be obtained using the molecular fingerprint information on individual species. However, the imaging speed is the bottleneck for the c...

Deep convolutional neural networks for tongue squamous cell carcinoma classification using Raman spectroscopy.

Photodiagnosis and photodynamic therapy
With deep convolutional neural networks and fiber optic Raman spectroscopy, this study presents a novel classification method that discriminates tongue squamous cell carcinoma (TSCC) from non-tumorous tissue. To achieve this purpose, 24 tissues spect...

High-Resolution Raman Microscopic Detection of Follicular Thyroid Cancer Cells with Unsupervised Machine Learning.

The journal of physical chemistry. B
We use Raman microscopic images with high spatial and spectral resolution to investigate differences between human follicular thyroid (Nthy-ori 3-1) and follicular thyroid carcinoma (FTC-133) cells, a well-differentiated thyroid cancer. Through compa...

Machine-Learning-Driven Surface-Enhanced Raman Scattering Optophysiology Reveals Multiplexed Metabolite Gradients Near Cells.

ACS nano
The extracellular environment is a complex medium in which cells secrete and consume metabolites. Molecular gradients are thereby created near cells, triggering various biological and physiological responses. However, investigating these molecular gr...