Deep learning and artificial intelligence methods for Raman and surface-enhanced Raman scattering
Abstract Machine learning is shaping up our lives in many ways. In analytical sciences,
machine learning provides an unprecedented opportunity to extract information from …
machine learning provides an unprecedented opportunity to extract information from …
Challenges in application of Raman spectroscopy to biology and materials
Raman spectroscopy has become an essential tool for chemists, physicists, biologists and
materials scientists. In this article, we present the challenges in unravelling the molecule …
materials scientists. In this article, we present the challenges in unravelling the molecule …
Clinical applications of infrared and Raman spectroscopy in the fields of cancer and infectious diseases
Analytical technologies that can improve disease diagnosis are highly sought after. Current
screening/diagnostic tests for several diseases are limited by their moderate diagnostic …
screening/diagnostic tests for several diseases are limited by their moderate diagnostic …
Dengue models based on machine learning techniques: A systematic literature review
Background Dengue modeling is a research topic that has increased in recent years. Early
prediction and decision-making are key factors to control dengue. This Systematic Literature …
prediction and decision-making are key factors to control dengue. This Systematic Literature …
One-dimensional deep convolutional neural network for mineral classification from Raman spectroscopy
Raman spectroscopy is often used for the composition determination and rapid classification
of materials because it can reflect the molecular information of materials. Its accuracy mainly …
of materials because it can reflect the molecular information of materials. Its accuracy mainly …
Analysis of hepatitis B virus infection in blood sera using Raman spectroscopy and machine learning
This study presents the analysis of hepatitis B virus (HBV) infection in human blood serum
using Raman spectroscopy combined with pattern recognition technique. In total, 119 …
using Raman spectroscopy combined with pattern recognition technique. In total, 119 …
Deep Learning–Assisted Surface-Enhanced Raman Scattering for Rapid Bacterial Identification
YM Tseng, KL Chen, PH Chao, YY Han… - ACS Applied Materials …, 2023 - ACS Publications
Bloodstream infection (BSI) is characterized by the presence of viable microorganisms in the
bloodstream and may induce systemic immune responses. Early and appropriate antibiotic …
bloodstream and may induce systemic immune responses. Early and appropriate antibiotic …
MaxViT-UNet: Multi-axis attention for medical image segmentation
Since their emergence, Convolutional Neural Networks (CNNs) have made significant
strides in medical image analysis. However, the local nature of the convolution operator may …
strides in medical image analysis. However, the local nature of the convolution operator may …
Analysis of tuberculosis disease through Raman spectroscopy and machine learning
We present the effectiveness of Raman spectroscopy (RS) in combination with machine
learning for screening and analysis of blood sera collected from tuberculosis patients. Blood …
learning for screening and analysis of blood sera collected from tuberculosis patients. Blood …
Cost effective and efficient screening of tuberculosis disease with Raman spectroscopy and machine learning algorithms
R Ullah, S Khan, II Chaudhary, S Shahzad, H Ali… - Photodiagnosis and …, 2020 - Elsevier
The current study presents Raman Spectroscopy (RS) accompanied by machine learning
algorithms based on Principle Component Analysis (PCA) and Hierarchical Cluster Analysis …
algorithms based on Principle Component Analysis (PCA) and Hierarchical Cluster Analysis …