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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 …
Artificial intelligence in neurodegenerative diseases: A review of available tools with a focus on machine learning techniques
Neurodegenerative diseases have shown an increasing incidence in the older population in
recent years. A significant amount of research has been conducted to characterize these …
recent years. A significant amount of research has been conducted to characterize these …
Identifying autism spectrum disorder with multi-site fMRI via low-rank domain adaptation
Autism spectrum disorder (ASD) is a neurodevelopmental disorder that is characterized by a
wide range of symptoms. Identifying biomarkers for accurate diagnosis is crucial for early …
wide range of symptoms. Identifying biomarkers for accurate diagnosis is crucial for early …
[HTML][HTML] Predictive markers for Parkinson's disease using deep neural nets on neuromelanin sensitive MRI
Neuromelanin sensitive magnetic resonance imaging (NMS-MRI) has been crucial in
identifying abnormalities in the substantia nigra pars compacta (SNc) in Parkinson's disease …
identifying abnormalities in the substantia nigra pars compacta (SNc) in Parkinson's disease …
Exploiting macro-and micro-structural brain changes for improved Parkinson's disease classification from MRI data
Parkinson's disease (PD) is the second most common neurodegenerative disease. Accurate
PD diagnosis is crucial for effective treatment and prognosis but can be challenging …
PD diagnosis is crucial for effective treatment and prognosis but can be challenging …
Bayesian optimization with support vector machine model for parkinson disease classification
Parkinson's disease (PD) has become widespread these days all over the world. PD affects
the nervous system of the human and also affects a lot of human body parts that are …
the nervous system of the human and also affects a lot of human body parts that are …
Quantifying Parkinson's disease motor severity under uncertainty using MDS-UPDRS videos
Parkinson's disease (PD) is a brain disorder that primarily affects motor function, leading to
slow movement, tremor, and stiffness, as well as postural instability and difficulty with …
slow movement, tremor, and stiffness, as well as postural instability and difficulty with …
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 …
Review of classical dimensionality reduction and sample selection methods for large-scale data processing
X Xu, T Liang, J Zhu, D Zheng, T Sun - Neurocomputing, 2019 - Elsevier
In the era of big data, all types of data with increasing samples and high-dimensional
attributes are demonstrating their important roles in various fields, such as data mining …
attributes are demonstrating their important roles in various fields, such as data mining …
[HTML][HTML] Explainable classification of Parkinson's disease using deep learning trained on a large multi-center database of T1-weighted MRI datasets
Introduction Parkinson's disease (PD) is a severe neurodegenerative disease that affects
millions of people. Early diagnosis is important to facilitate prompt interventions to slow …
millions of people. Early diagnosis is important to facilitate prompt interventions to slow …