Neuroinformatics is a fascinating research field that applies computational models and
analytical tools to high dimensional experimental neuroscience data for a better …

Neuroinformatics is a fascinating research field that applies computational models and
analytical tools to high dimensional experimental neuroscience data for a better …

Neuroinformatics is a fascinating research field that applies computational models and
analytical tools to high dimensional experimental neuroscience data for a better …

Objective: Machine learning classification has been the most important computational
development in the last years to satisfy the primary need of clinicians for automatic early …

Random Forest (RF) is a bagging ensemble model and has many important advantages,
such as robustness to noise, an effective structure for complex multimodal data and parallel …

Computer-aided diagnosis of Alzheimer's disease (AD) is a rapidly developing field of
neuroimaging with strong potential to be used in practice. In this context, assessment of …

In this study, we propose a novel sparse regression based random forest (RF) to predict
future clinical scores of Alzheimer's disease (AD) with the baseline scores and the MRI …

Background In the era of computer-assisted diagnostic tools for various brain diseases,
Alzheimer's disease (AD) covers a large percentage of neuroimaging research, with the …

Background: Early detection of Alzheimer's disease (AD) based on integrating information
from different sources has become an intensive area of research. Machine learning …

Background Alzheimer's disease (AD) is the most common cause of dementia in the elderly
and affects approximately 30 million individuals worldwide. Mild cognitive impairment (MCI) …