AIMC Topic: Discriminant Analysis

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Deriving accurate molecular indicators of protein synthesis through Raman-based sparse classification.

The Analyst May 4, 2021
Raman spectroscopy has the ability to retrieve molecular information from live biological samples non-invasively through optical means. Coupled with machine learning, it is possible to use this large amount of information to create models that can pr...
Spectrum Analysis, Raman Principal Component Analysis Discriminant Analysis Machine Learning
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Diagnosis of Alzheimer's Disease Severity with fMRI Images Using Robust Multitask Feature Extraction Method and Convolutional Neural Network (CNN).

Computational and mathematical methods in medicine Apr 27, 2021
The automatic diagnosis of Alzheimer's disease plays an important role in human health, especially in its early stage. Because it is a neurodegenerative condition, Alzheimer's disease seems to have a long incubation period. Therefore, it is essential...
Severity of Illness Index Algorithms Humans Alzheimer Disease Computational Biology Databases, Factual Deep Learning Image Interpretation, Computer-Assisted Neural Networks, Computer Brain Functional Neuroimaging Early Diagnosis Decision Trees Mental Status and Dementia Tests Support Vector Machine Discriminant Analysis Magnetic Resonance Imaging
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Diagnosis of Alzheimer's Disease by Time-Dependent Power Spectrum Descriptors and Convolutional Neural Network Using EEG Signal.

Computational and mathematical methods in medicine Apr 23, 2021
Using strategies that obtain biomarkers where early symptoms coincide, the early detection of Alzheimer's disease and its complications is essential. Electroencephalogram is a technology that allows thousands of neurons with equal spatial orientation...
Alzheimer Disease Early Diagnosis Case-Control Studies Discriminant Analysis Diagnosis, Computer-Assisted Electroencephalography Signal Processing, Computer-Assisted Cognitive Dysfunction Humans Computational Biology Neural Networks, Computer Support Vector Machine
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Development of a portable oil type classifier using laser-induced fluorescence spectrometer coupled with chemometrics.

Journal of hazardous materials Mar 23, 2021
Due to the recurrent small spills, oil pollution along coastal regions is still a major environmental issue. Standardized oil fingerprinting techniques are useful for oil spill identifications, but time- and resource-consuming. There have been ongoin...
Reproducibility of Results Support Vector Machine Least-Squares Analysis Discriminant Analysis Lasers
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Classification of Greek Olive Oils from Different Regions by Machine Learning-Aided Laser-Induced Breakdown Spectroscopy and Absorption Spectroscopy.

Molecules (Basel, Switzerland) Feb 25, 2021
In the present work, the emission and the absorption spectra of numerous Greek olive oil samples and mixtures of them, obtained by two spectroscopic techniques, namely Laser-Induced Breakdown Spectroscopy (LIBS) and Absorption Spectroscopy, and aided...
Machine Learning Spectroscopy, Near-Infrared Olive Oil Greece Spectrophotometry, Atomic Principal Component Analysis Discriminant Analysis Linear Models Spectrophotometry, Ultraviolet
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On the estimation of sugars concentrations using Raman spectroscopy and artificial neural networks.

Food chemistry Feb 24, 2021
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...
Sugars Discriminant Analysis Linear Models Neural Networks, Computer Water Spectrum Analysis, Raman Support Vector Machine Least-Squares Analysis
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A graphical user interface (NWUSA) for Raman spectral processing, analysis and feature recognition.

Journal of biophotonics Feb 18, 2021
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...
Least-Squares Analysis Discriminant Analysis Spectrum Analysis, Raman Support Vector Machine Algorithms Principal Component Analysis
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A Review of the Discriminant Analysis Methods for Food Quality Based on Near-Infrared Spectroscopy and Pattern Recognition.

Molecules (Basel, Switzerland) Feb 1, 2021
Near-infrared spectroscopy (NIRS) combined with pattern recognition technique has become an important type of non-destructive discriminant method. This review first introduces the basic structure of the qualitative analysis process based on near-infr...
Discriminant Analysis Humans Pattern Recognition, Automated Neural Networks, Computer Food Quality Spectroscopy, Near-Infrared Food Analysis
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Discrimination of Malaysian stingless bee honey from different entomological origins based on physicochemical properties and volatile compound profiles using chemometrics and machine learning.

Food chemistry Jan 15, 2021
Identification of honey origin based on specific chemical markers is important for honey authentication. This study is aimed to differentiate Malaysian stingless bee honey from different entomological origins (Heterotrigona bakeri, Geniotrigona thora...
Machine Learning Animals Phylogeny Cluster Analysis Honey Volatile Organic Compounds Bees Principal Component Analysis Least-Squares Analysis Discriminant Analysis
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Evaluation of wavelength ranges and tissue depth probed by diffuse reflectance spectroscopy for colorectal cancer detection.

Scientific reports Jan 12, 2021
Colorectal cancer (CRC) is the third most common type of cancer worldwide and the second most deadly. Recent research efforts have focused on developing non-invasive techniques for CRC detection. In this study, we evaluated the diagnostic capabilitie...
Spectrophotometry Middle Aged Support Vector Machine Humans Discriminant Analysis Algorithms Colorectal Neoplasms Aged Female Male Aged, 80 and over Adult
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