Multi-view learning (MVL) has attracted increasing attention and achieved great practical
success by exploiting complementary information of multiple features or modalities …

Electroencephalography (EEG)-based brain-computer interfaces (BCIs), particularly those
using motor-imagery (MI) data, have the potential to become groundbreaking technologies …

Simple Summary Deep learning has succeeded greatly in medical image-based cancer
diagnosis. To help readers better understand the current research status and ideas, this …

Superior feature extraction, channel selection and classification methods are essential for
designing electroencephalography (EEG) classification frameworks. However, the …

In the treatment of cancers, the efficacy depends on the correct diagnosis of the nature of
tumor as early as possible. Micro-array Gene expression data which contains the expression …

In the field of microarray data research, it is quite challenging to make classification due to
small sample size and the high dimension of data. Moreover, the feature selection is crucial …

En la actualidad, en el ámbito sanitario, hay un interés creciente en la consideración de
técnicas de Inteligencia Artificial, en concreto técnicas de Aprendizaje Automático o …

Multiple sourced data is commonly available with different measuring methods in this digital
era. Usually, the dataset analysis is performed by combining multiple source data, which …

Correct classification of tumors is an important problem in clinical oncology. Availability of
gene expression profiles from DNA microarray experiments has made it possible to use …