Alzheimer's disease is an incurable neurodegenerative disease primarily affecting the
elderly population. Efficient automated techniques are needed for early diagnosis of …

Background. Alzheimer's disease (AD) is a progressive neurodegenerative disorder
affecting many individuals worldwide with no effective treatment to date. AD is characterized …

Mounting evidence has highlighted the implementation of big data handling and
management in the healthcare industry to improve the clinical services. Various private and …

Recent studies on brain imaging analysis witnessed the core roles of machine learning
techniques in computer-assisted intervention for brain disease diagnosis. Of various …

The idea that the purely phenomenological knowledge that we can extract by analyzing
large amounts of data can be useful in healthcare seems to contradict the desire of VPH …

Alzheimer's disease is one of the most common causes of death in today's world. Magnetic
resonance imaging (MRI) provides an efficient and non-invasive approach for diagnosis of …

Background/objectives: Neurofilament light chain (NfL) levels in the cerebrospinal fluid
(CSF) of multiple sclerosis (MS) patients correlate with the degree of neuronal injury. To …

Background Mild cognitive impairment (MCI) due to Alzheimer's disease is the symptomatic
predementia phase of Alzheimer's disease dementia, characterised by cognitive and …

In this paper, we provide an extensive overview of machine learning techniques applied to
structural magnetic resonance imaging (MRI) data to obtain clinical classifiers. We …

Combining machine learning with neuroimaging data has a great potential for early
diagnosis of mild cognitive impairment (MCI) and Alzheimer's disease (AD). However, it …