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Machine learning for the diagnosis of Parkinson's disease: a review of literature
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 …
assessment of clinical signs, including the characterization of a variety of motor symptoms …
[HTML][HTML] From recognition to remedy: The significance of biomarkers in neurodegenerative disease pathology
C Toader, N Dobrin, FM Brehar, C Popa… - International Journal of …, 2023 - mdpi.com
With the inexorable aging of the global populace, neurodegenerative diseases (NDs) like
Alzheimer's disease (AD), Parkinson's disease (PD), and amyotrophic lateral sclerosis (ALS) …
Alzheimer's disease (AD), Parkinson's disease (PD), and amyotrophic lateral sclerosis (ALS) …
Magnetic resonance imaging for the diagnosis of Parkinson's disease
B Heim, F Krismer, R De Marzi, K Seppi - Journal of neural transmission, 2017 - Springer
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 …
challenging in neurology and error rates in the clinical diagnosis can be high even at …
[HTML][HTML] Resting-state connectivity in neurodegenerative disorders: Is there potential for an imaging biomarker?
Biomarkers in whichever modality are tremendously important in diagnosing of disease,
tracking disease progression and clinical trials. This applies in particular for disorders with a …
tracking disease progression and clinical trials. This applies in particular for disorders with a …
Resting-state fMRI in Parkinson's disease patients with cognitive impairment: a meta-analysis
AF Wolters, SCF van de Weijer, AFG Leentjens… - Parkinsonism & related …, 2019 - Elsevier
Background Cognitive impairment is a common non-motor symptom in Parkinson's disease.
So far, the underlying pathophysiology remains unclear. Several alterations in functional …
So far, the underlying pathophysiology remains unclear. Several alterations in functional …
Mining imaging and clinical data with machine learning approaches for the diagnosis and early detection of Parkinson's disease
J Zhang - npj Parkinson's Disease, 2022 - nature.com
Parkinson's disease (PD) is a common, progressive, and currently incurable
neurodegenerative movement disorder. The diagnosis of PD is challenging, especially in …
neurodegenerative movement disorder. The diagnosis of PD is challenging, especially in …
A systematic review of artificial intelligence (AI) based approaches for the diagnosis of Parkinson's disease
Parkinson's disease (PD) is a neurodegenerative disorder that primarily affects the elderly
for over 55 years. PD can be characterised by patients exhibiting various non-motor and …
for over 55 years. PD can be characterised by patients exhibiting various non-motor and …
Resting‐state functional MRI in parkinsonian syndromes
ABSTRACT Background Functional MRI (fMRI) has been widely used to study abnormal
patterns of functional connectivity at rest in patients with movement disorders such as …
patterns of functional connectivity at rest in patients with movement disorders such as …
Exploring the reproducibility of functional connectivity alterations in Parkinson's disease
L Badea, M Onu, T Wu, A Roceanu, O Bajenaru - PLoS One, 2017 - journals.plos.org
Since anatomic MRI is presently not able to directly discern neuronal loss in Parkinson's
Disease (PD), studying the associated functional connectivity (FC) changes seems a …
Disease (PD), studying the associated functional connectivity (FC) changes seems a …
Machine learning approaches to identify affected brain regions in movement disorders using MRI data: A systematic review and diagnostic meta‐analysis
Background Movement disorders such as Parkinson's disease are associated with structural
and functional changes in specific brain regions. Advanced magnetic resonance imaging …
and functional changes in specific brain regions. Advanced magnetic resonance imaging …