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Principal Component Analysis

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Spectrochemical analysis of blood combined with chemometric techniques for detecting osteosarcopenia.

Scientific reports
Among several complications related to physiotherapy, osteosarcopenia is one of the most frequent in elderly patients. This condition is limiting and quite harmful to the patient's health by disabling several basic musculoskeletal activities. Current...

Principal component analysis-multivariate adaptive regression splines (PCA-MARS) and back propagation-artificial neural network (BP-ANN) methods for predicting the efficiency of oxidative desulfurization systems using ATR-FTIR spectroscopy.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
Oxidative desulfurization (ODS) of diesel fuels has received attention in recent years due to mild working conditions and effective removal of the aromatic sulfur compounds. There is a need for rapid, accurate, and reproducible analytical tools to mo...

Rapid detection of cholecystitis by serum fluorescence spectroscopy combined with machine learning.

Journal of biophotonics
While cholecystitis is a critical public health problem, the conventional diagnostic methods for its detection are time consuming, expensive and insufficiently sensitive. This study examined the possibility of using serum fluorescence spectroscopy an...

Raman spectroscopy combined with a support vector machine algorithm as a diagnostic technique for primary Sjögren's syndrome.

Scientific reports
The aim of this study was to explore the feasibility of Raman spectroscopy combined with computer algorithms in the diagnosis of primary Sjögren syndrome (pSS). In this study, Raman spectra of 60 serum samples were acquired from 30 patients with pSS ...

Hybrid autoencoder with orthogonal latent space for robust population structure inference.

Scientific reports
Analysis of population structure and genomic ancestry remains an important topic in human genetics and bioinformatics. Commonly used methods require high-quality genotype data to ensure accurate inference. However, in practice, laboratory artifacts a...

Mutual Information-Driven Feature Reduction for Hyperspectral Image Classification.

Sensors (Basel, Switzerland)
A hyperspectral image (HSI), which contains a number of contiguous and narrow spectral wavelength bands, is a valuable source of data for ground cover examinations. Classification using the entire original HSI suffers from the "curse of dimensionalit...

Study on the classification and identification of various carbonate and sulfate mineral medicines based on Raman spectroscopy combined with PCA-SVM algorithm.

Analytical sciences : the international journal of the Japan Society for Analytical Chemistry
The efficacy of mineral medicines varies greatly between different origins. Therefore, investigating a method to quickly identify similar mineral medicines is meaningful. In this paper, a visual classification and identification model of Raman spectr...

The harmonium model and its unified system view of psychopathology: a validation study by means of a convolutional neural network.

Scientific reports
The harmonium model (HM) is a recent conceptualization of the unifying view of psychopathology, namely the idea of a general mechanism underpinning all mental disorders (the p factor). According to HM, psychopathology consists of a low dimensional Ph...

Classification of Gravity Matching Areas Using PSO-BP Neural Networks based on PCA and Satellite Altimetry Data over the Western Pacific.

Sensors (Basel, Switzerland)
For inertial navigation systems (INS), as one of the major methods for underwater navigation, errors diverge over time. With the development of geophysical navigation technology, gravity navigation has become an effective method of navigation. Signif...

Water consumption prediction and influencing factor analysis based on PCA-BP neural network in karst regions: a case study of Guizhou Province.

Environmental science and pollution research international
Water consumption prediction is an integral part of water resource planning and management. Constructing a highly precise water consumption prediction model is of great significance for promoting regional water resource planning and high-quality deve...