AI Medical Compendium Topic

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Principal Component Analysis

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A Guided Tutorial on Modelling Human Event-Related Potentials with Recurrent Neural Networks.

Sensors (Basel, Switzerland)
In cognitive neuroscience research, computational models of event-related potentials (ERP) can provide a means of developing explanatory hypotheses for the observed waveforms. However, researchers trained in cognitive neurosciences may face technical...

Deep neural network-based structural health monitoring technique for real-time crack detection and localization using strain gauge sensors.

Scientific reports
Structural health monitoring (SHM) techniques often require a large number of sensors to evaluate and monitor the structural health. In this paper, we propose a deep neural network (DNN)-based SHM method for accurate crack detection and localization ...

Deep Learning Model for the Image Fusion and Accurate Classification of Remote Sensing Images.

Computational intelligence and neuroscience
Deep learning is widely used for the classification of images that have various attributes. Image data are used to extract colour, texture, form, and local features. These features are combined in feature-level image fusion to create a merged remote ...

A New Mixed-Gas-Detection Method Based on a Support Vector Machine Optimized by a Sparrow Search Algorithm.

Sensors (Basel, Switzerland)
To solve the problem of the low recognition rate of mixed gases and consider the phenomenon of low prediction accuracy when traditional gas-concentration-prediction methods deal with nonlinear data, this paper proposes a mixed-gas identification and ...

Rolling Bearing Fault Diagnosis Using Hybrid Neural Network with Principal Component Analysis.

Sensors (Basel, Switzerland)
With the rapid development of fault prognostics and health management (PHM) technology, more and more deep learning algorithms have been applied to the intelligent fault diagnosis of rolling bearings, and although all of them can achieve over 90% dia...

Machine learning of pair-contact process with diffusion.

Scientific reports
The pair-contact process with diffusion (PCPD), a generalized model of the ordinary pair-contact process (PCP) without diffusion, exhibits a continuous absorbing phase transition. Unlike the PCP, whose nature of phase transition is clearly classified...

Unsupervised classification of voltammetric data beyond principal component analysis.

Chemical communications (Cambridge, England)
In this study, we evaluate different apoproaches to unsupervised classification of cyclic voltammetric data, including Principal Component Analysis (PCA), t-distributed Stochastic Neighbour Embedding (t-SNE), Uniform Manifold Approximation and Projec...

Is handling unbalanced datasets for machine learning uplifts system performance?: A case of diabetic prediction.

Diabetes & metabolic syndrome
BACKGROUND AND AIMS: Healthcare is a sensitive sector, and addressing the class imbalance in the healthcare domain is a time-consuming task for machine learning-based systems due to the vast amount of data. This study looks into the impact of socioec...

Optimization and Application of Information Visualization Design Based on Image Symbol under the Guidance of Feature Integration Theory.

Contrast media & molecular imaging
Increasingly, today's businesses rely on data visualization to aid in the outcome that is directly linked to the bulk of their earnings. Due to the enormous volume, speed, and accuracy requirements of data management, database professionals are becom...

Haplotype and population structure inference using neural networks in whole-genome sequencing data.

Genome research
Accurate inference of population structure is important in many studies of population genetics. Here we present HaploNet, a method for performing dimensionality reduction and clustering of genetic data. The method is based on local clustering of phas...