Diagnosis of Parkinson's disease (PD) is commonly based on medical observations and
assessment of clinical signs, including the characterization of a variety of motor symptoms …

Standard univariate analysis of neuroimaging data has revealed a host of neuroanatomical
and functional differences between healthy individuals and patients suffering a wide range …

The differential diagnosis of parkinsonian syndromes is considered one of the most
challenging in neurology and error rates in the clinical diagnosis can be high even at …

ABSTRACT PSP is a pathologically defined neurodegenerative tauopathy with a variety of
clinical presentations including typical Richardson's syndrome and other variant PSP …

Determination of sensitive and specific markers of very early AD progression is intended to
aid researchers and clinicians to develop new treatments and monitor their effectiveness, as …

Background Supervised machine learning has been proposed as a revolutionary approach
for identifying sensitive medical image biomarkers (or combination of them) allowing for …

Parkinson's disease (PD) is a common, progressive, and currently incurable
neurodegenerative movement disorder. The diagnosis of PD is challenging, especially in …

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 …

Conventional single tensor diffusion analysis models have provided mixed findings in the
substantia nigra of Parkinson's disease, but recent work using a bi-tensor analysis model …

Background Parkinson's disease (PD) is a chronic neurodegenerative disorder
characterized by bradykinesia, tremor, and rigidity among other symptoms. With a 70 …