Subtle changes in fine motor control and quantitative electroencephalography (qEEG) in
patients with mild cognitive impairment (MCI) are important in screening for early dementia …

Precision medicine aims to integrate an individual's unique features from clinical
phenotypes and biological information obtained from imaging to laboratory tests and health …

Mild cognitive impairment is associated with many neurodegenerative diseases. It is
essential to detect mild cognitive impairment on time to reduce the prevalence of such …

Artificial Intelligence (AI) dramatically alters traditional healthcare and cognition assessment
with its power in ubiquitous perception and smart computation. However, the existing …

Early diagnosis of mild cognitive impairment (MCI) is critical for reducing the incidence of
serious neurodegenerative diseases. However, current diagnostic solutions, such as …

Background: Neuroimaging is an important tool in early detection of Alzheimer's disease
(AD), which is a serious neurodegenerative brain disease among the elderly subjects …

In this paper, we describe a novel machine learning method for classifying Alzheimer's
disease (AD), Mild cognitive impairment (MCI) and Normal Control (NC) subjects based on …

Due to the characteristics of high noise and low resolution in medical images, it is difficult to
extract local features, which affects the accuracy of image diagnosis and classification. To …

With the rapid development of medical industry, there is a growing demand for disease
diagnosis using machine learning technology. The recent success of deep learning brings it …

A neuroimaging feature extraction model is designed to extract region-based image features
whose values are predicted by base learners trained on raw neuroimaging morphological …