AIMC Topic: Principal Component Analysis

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Hybrid Network Model for "Deep Learning" of Chemical Data: Application to Antimicrobial Peptides.

Molecular informatics
We present a "deep" network architecture for chemical data analysis and classification together with a prospective proof-of-concept application. The model features a self-organizing map (SOM) as the input layer of a feedforward neural network. The SO...

Predicting ground contact events for a continuum of gait types: An application of targeted machine learning using principal component analysis.

Gait & posture
An ongoing challenge in the application of gait analysis to clinical settings is the standardized detection of temporal events, with unobtrusive and cost-effective equipment, for a wide range of gait types. The purpose of the current study was to inv...

Medical Decision Support System for Diagnosis of Heart Arrhythmia using DWT and Random Forests Classifier.

Journal of medical systems
In this study, Random Forests (RF) classifier is proposed for ECG heartbeat signal classification in diagnosis of heart arrhythmia. Discrete wavelet transform (DWT) is used to decompose ECG signals into different successive frequency bands. A set of ...

Early detection of germinated wheat grains using terahertz image and chemometrics.

Scientific reports
In this paper, we propose a feasible tool that uses a terahertz (THz) imaging system for identifying wheat grains at different stages of germination. The THz spectra of the main changed components of wheat grains, maltose and starch, which were obtai...

Multivariate Calibration Approach for Quantitative Determination of Cell-Line Cross Contamination by Intact Cell Mass Spectrometry and Artificial Neural Networks.

PloS one
Cross-contamination of eukaryotic cell lines used in biomedical research represents a highly relevant problem. Analysis of repetitive DNA sequences, such as Short Tandem Repeats (STR), or Simple Sequence Repeats (SSR), is a widely accepted, simple, a...

Oil species identification technique developed by Gabor wavelet analysis and support vector machine based on concentration-synchronous-matrix-fluorescence spectroscopy.

Marine pollution bulletin
Concentration-synchronous-matrix-fluorescence (CSMF) spectroscopy was applied to discriminate the oil species by characterizing the concentration dependent fluorescence properties of petroleum related samples. Seven days weathering experiment of 3 cr...

Support vector regression to estimate the permeability enhancement of potential transdermal enhancers.

The Journal of pharmacy and pharmacology
OBJECTIVES: Searching for chemicals that will safely enhance transdermal drug delivery is a significant challenge. This study applies support vector regression (SVR) for the first time to estimating the optimal formulation design of transdermal hydro...

Predicting Drug-Target Interactions With Multi-Information Fusion.

IEEE journal of biomedical and health informatics
Identifying potential associations between drugs and targets is a critical prerequisite for modern drug discovery and repurposing. However, predicting these associations is difficult because of the limitations of existing computational methods. Most ...