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Principal Component Analysis

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The effect of principal component analysis in the diagnosis of congestive heart failure via heart rate variability analysis.

Proceedings of the Institution of Mechanical Engineers. Part H, Journal of engineering in medicine
In this study, we investigated the effect of principal component analysis (PCA) in congestive heart failure (CHF) diagnosis using various machine learning algorithms from 5-min HRV data. The extracted 59 heart rate variability (HRV) features consist ...

The application of feature engineering in establishing a rapid and robust model for identifying patients with glioma.

Lasers in medical science
The aim of the study is to evaluate the efficacy of the combination of Raman spectroscopy with feature engineering and machine learning algorithms for detecting glioma patients. In this study, we used Raman spectroscopy technology to collect serum sp...

DeepBeam: a machine learning framework for tuning the primary electron beam of the PRIMO Monte Carlo software.

Radiation oncology (London, England)
BACKGROUND: Any Monte Carlo simulation of dose delivery using medical accelerator-generated megavolt photon beams begins by simulating electrons of the primary electron beam interacting with a target. Because the electron beam characteristics of any ...

Machine learning classification of origins and varieties of Tetrastigma hemsleyanum using a dual-mode microscopic hyperspectral imager.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
A dual-mode microscopic hyperspectral imager (DMHI) combined with a machine learning algorithm for the purpose of classifying origins and varieties of Tetrastigma hemsleyanum (T. hemsleyanum) was developed. By switching the illumination source, the D...

FTIR spectroscopy with machine learning: A new approach to animal DNA polymorphism screening.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
Technological advances in recent decades, especially in molecular genetics, have enabled the detection of genetic DNA markers associated with productive characteristics in animals. However, the prospection of polymorphisms based on DNA sequencing is ...

Designing a hybrid dimension reduction for improving the performance of Amharic news document classification.

PloS one
The volume of Amharic digital documents has grown rapidly in recent years. As a result, automatic document categorization is highly essential. In this paper, we present a novel dimension reduction approach for improving classification accuracy by com...

Fast and accurate automated recognition of the dominant cells from fecal images based on Faster R-CNN.

Scientific reports
Fecal samples can easily be collected and are representative of a person's current health state; therefore, the demand for routine fecal examination has increased sharply. However, manual operation may pollute the samples, and low efficiency limits t...

Self-organising maps for the exploration and classification of thin-layer chromatograms.

Talanta
Thin-layer chromatography (TLC) allows the swift analysis of larger sample sets in almost any laboratory. The obtained chromatograms are patterns of coloured zones that are conveniently evaluated and classified by visual inspection. This manual appro...