AIMC Topic: Algorithms

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Passivity analysis of delayed reaction-diffusion memristor-based neural networks.

Neural networks : the official journal of the International Neural Network Society
This paper discusses the passivity of delayed reaction-diffusion memristor-based neural networks (RDMNNs). By exploiting inequality techniques and by constructing appropriate Lyapunov functional, several sufficient conditions are obtained in the form...

Comparative Evaluation of Machine Learning Strategies for Analyzing Big Data in Psychiatry.

International journal of molecular sciences
The requirement of innovative big data analytics has become a critical success factor for research in biological psychiatry. Integrative analyses across distributed data resources are considered essential for untangling the biological complexity of m...

An Improved Fuzzy Connectedness Method for Automatic Three-Dimensional Liver Vessel Segmentation in CT Images.

Journal of healthcare engineering
In this paper, an improved fuzzy connectedness (FC) method was proposed for automatic three-dimensional (3D) liver vessel segmentation in computed tomography (CT) images. The vessel-enhanced image (i.e., vesselness image) was incorporated into the fu...

A neurodynamic approach to nonlinear optimization problems with affine equality and convex inequality constraints.

Neural networks : the official journal of the International Neural Network Society
This paper presents a neurodynamic approach to nonlinear optimization problems with affine equality and convex inequality constraints. The proposed neural network endows with a time-varying auxiliary function, which can guarantee that the state of th...

A collaborative computer aided diagnosis (C-CAD) system with eye-tracking, sparse attentional model, and deep learning.

Medical image analysis
Computer aided diagnosis (CAD) tools help radiologists to reduce diagnostic errors such as missing tumors and misdiagnosis. Vision researchers have been analyzing behaviors of radiologists during screening to understand how and why they miss tumors o...

Sparse Representation-Based Extreme Learning Machine for Motor Imagery EEG Classification.

Computational intelligence and neuroscience
Classification of motor imagery (MI) electroencephalogram (EEG) plays a vital role in brain-computer interface (BCI) systems. Recent research has shown that nonlinear classification algorithms perform better than their linear counterparts, but most o...

Machine Learning for Predicting Cognitive Diseases: Methods, Data Sources and Risk Factors.

Journal of medical systems
Machine learning and data mining approaches are being successfully applied to different fields of life sciences for the past 20 years. Medicine is one of the most suitable application domains for these techniques since they help model diagnostic info...

Pulmonary CT Registration Through Supervised Learning With Convolutional Neural Networks.

IEEE transactions on medical imaging
Deformable image registration can be time consuming and often needs extensive parameterization to perform well on a specific application. We present a deformable registration method based on a 3-D convolutional neural network, together with a framewo...

3D regression neural network for the quantification of enlarged perivascular spaces in brain MRI.

Medical image analysis
Enlarged perivascular spaces (EPVS) in the brain are an emerging imaging marker for cerebral small vessel disease, and have been shown to be related to increased risk of various neurological diseases, including stroke and dementia. Automated quantifi...

Automated Algorithm Selection on Continuous Black-Box Problems by Combining Exploratory Landscape Analysis and Machine Learning.

Evolutionary computation
In this article, we build upon previous work on designing informative and efficient Exploratory Landscape Analysis features for characterizing problems' landscapes and show their effectiveness in automatically constructing algorithm selection models ...