AIMC Topic: Machine Learning

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A Deep Learning Scheme for Motor Imagery Classification based on Restricted Boltzmann Machines.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Motor imagery classification is an important topic in brain-computer interface (BCI) research that enables the recognition of a subject's intension to, e.g., implement prosthesis control. The brain dynamics of motor imagery are usually measured by el...

A machine learning strategy for predicting localization of post-translational modification sites in protein-protein interacting regions.

BMC bioinformatics
BACKGROUND: One very important functional domain of proteins is the protein-protein interacting region (PPIR), which forms the binding interface between interacting polypeptide chains. Post-translational modifications (PTMs) that occur in the PPIR ca...

Sorting protein decoys by machine-learning-to-rank.

Scientific reports
Much progress has been made in Protein structure prediction during the last few decades. As the predicted models can span a broad range of accuracy spectrum, the accuracy of quality estimation becomes one of the key elements of successful protein str...

Deep Convolutional Extreme Learning Machine and Its Application in Handwritten Digit Classification.

Computational intelligence and neuroscience
In recent years, some deep learning methods have been developed and applied to image classification applications, such as convolutional neuron network (CNN) and deep belief network (DBN). However they are suffering from some problems like local minim...

Advanced Online Survival Analysis Tool for Predictive Modelling in Clinical Data Science.

PloS one
One of the prevailing applications of machine learning is the use of predictive modelling in clinical survival analysis. In this work, we present our view of the current situation of computer tools for survival analysis, stressing the need of transfe...

Problematic internet use (PIU): Associations with the impulsive-compulsive spectrum. An application of machine learning in psychiatry.

Journal of psychiatric research
Problematic internet use is common, functionally impairing, and in need of further study. Its relationship with obsessive-compulsive and impulsive disorders is unclear. Our objective was to evaluate whether problematic internet use can be predicted f...

Role of Muscle Synergies in Real-Time Classification of Upper Limb Motions using Extreme Learning Machines.

Journal of neuroengineering and rehabilitation
BACKGROUND: Myoelectric signals offer significant insights in interpreting the motion intention and extent of effort involved in performing a movement, with application in prostheses, orthosis and exoskeletons. Feature extraction plays a vital role, ...

Liver Tumor Segmentation from MR Images Using 3D Fast Marching Algorithm and Single Hidden Layer Feedforward Neural Network.

BioMed research international
Objective. Our objective is to develop a computerized scheme for liver tumor segmentation in MR images. Materials and Methods. Our proposed scheme consists of four main stages. Firstly, the region of interest (ROI) image which contains the liver tumo...

Extensive complementarity between gene function prediction methods.

Bioinformatics (Oxford, England)
MOTIVATION: The number of sequenced genomes rises steadily but we still lack the knowledge about the biological roles of many genes. Automated function prediction (AFP) is thus a necessity. We hypothesized that AFP approaches that draw on distinct ge...