Ensemble learning combines several individual models to obtain better generalization
performance. Currently, deep learning architectures are showing better performance …

The remarkable flexibility and adaptability of ensemble methods and deep learning models
have led to the proliferation of their application in bioinformatics research. Traditionally …

Breast cancers are complex ecosystems of malignant cells and the tumour
microenvironment. The composition of these tumour ecosystems and interactions within …

Recently, the whole world became infected by the newly discovered coronavirus (COVID-
19). SARS-CoV-2, or widely known as COVID-19, has proved to be a hazardous virus …

COVID-19 continues to have catastrophic effects on the lives of human beings throughout
the world. To combat this disease it is necessary to screen the affected patients in a fast and …

Abstract Over the years, Machine Learning models have been successfully employed on
neuroimaging data for accurately predicting brain age. Deviations from the healthy brain …

This work presents an efficient yet effective online Knowledge Distillation method via
Collaborative Learning, termed KDCL, which is able to consistently improve the …

Deep learning is a class of machine learning methods that has been successful in computer
vision. Unlike traditional machine learning methods that require hand-engineered feature …

Owing to improvements in image recognition via deep learning, machine-learning
algorithms could eventually be applied to automated medical diagnoses that can guide …

The automatic detection of diseases in plants is necessary, as it reduces the tedious work of
monitoring large farms and it will detect the disease at an early stage of its occurrence to …