AIMC Topic: Algorithms

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Instance Transfer Subject-Dependent Strategy for Motor Imagery Signal Classification Using Deep Convolutional Neural Networks.

Computational and mathematical methods in medicine
In the process of brain-computer interface (BCI), variations across sessions/subjects result in differences in the properties of potential of the brain. This issue may lead to variations in feature distribution of electroencephalogram (EEG) across su...

MGAT: Multi-view Graph Attention Networks.

Neural networks : the official journal of the International Neural Network Society
Multi-view graph embedding is aimed at learning low-dimensional representations of nodes that capture various relationships in a multi-view network, where each view represents a type of relationship among nodes. Multitudes of existing graph embedding...

Predicting Coronavirus Disease 2019 Infection Risk and Related Risk Drivers in Nursing Homes: A Machine Learning Approach.

Journal of the American Medical Directors Association
OBJECTIVE: Inform coronavirus disease 2019 (COVID-19) infection prevention measures by identifying and assessing risk and possible vectors of infection in nursing homes (NHs) using a machine-learning approach.

A machine-learning algorithm for neonatal seizure recognition: a multicentre, randomised, controlled trial.

The Lancet. Child & adolescent health
BACKGROUND: Despite the availability of continuous conventional electroencephalography (cEEG), accurate diagnosis of neonatal seizures is challenging in clinical practice. Algorithms for decision support in the recognition of neonatal seizures could ...

Gait Phase Recognition Using Deep Convolutional Neural Network with Inertial Measurement Units.

Biosensors
Gait phase recognition is of great importance in the development of assistance-as-needed robotic devices, such as exoskeletons. In order for a powered exoskeleton with phase-based control to determine and provide proper assistance to the wearer durin...

Application of Machine Learning Methods in Nursing Home Research.

International journal of environmental research and public health
A machine learning (ML) system is able to construct algorithms to continue improving predictions and generate automated knowledge through data-driven predictors or decisions. Objective: The purpose of this study was to compare six ML methods (random...

A novel machine learning strategy for model selections - Stepwise Support Vector Machine (StepSVM).

PloS one
An essential aspect of medical research is the prediction for a health outcome and the scientific identification of important factors. As a result, numerous methods were developed for model selections in recent years. In the era of big data, machine ...

Design of a hybrid ANN multi-objective whale algorithm for suspended sediment load prediction.

Environmental science and pollution research international
There is a need to develop an accurate and reliable model for predicting suspended sediment load (SSL) because of its complexity and difficulty in practice. This is due to the fact that sediment transportation is extremely nonlinear and is directed b...

White learning methodology: A case study of cancer-related disease factors analysis in real-time PACS environment.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Bayesian network is a probabilistic model of which the prediction accuracy may not be one of the highest in the machine learning family. Deep learning (DL) on the other hand possess of higher predictive power than many other...