Machine learning for the diagnosis of Parkinson's disease: a review of literature

J Mei, C Desrosiers, J Frasnelli - Frontiers in aging neuroscience, 2021 - frontiersin.org
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 …

Artificial intelligence in neurodegenerative diseases: A review of available tools with a focus on machine learning techniques

AM Tăuţan, B Ionescu, E Santarnecchi - Artificial intelligence in medicine, 2021 - Elsevier
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 …

Identifying autism spectrum disorder with multi-site fMRI via low-rank domain adaptation

M Wang, D Zhang, J Huang, PT Yap… - IEEE transactions on …, 2019 - ieeexplore.ieee.org
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 …

[HTML][HTML] Predictive markers for Parkinson's disease using deep neural nets on neuromelanin sensitive MRI

S Shinde, S Prasad, Y Saboo, R Kaushick, J Saini… - NeuroImage: Clinical, 2019 - Elsevier
Neuromelanin sensitive magnetic resonance imaging (NMS-MRI) has been crucial in
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

M Camacho, M Wilms, H Almgren, K Amador… - npj Parkinson's …, 2024 - nature.com
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 …

Bayesian optimization with support vector machine model for parkinson disease classification

AM Elshewey, MY Shams, N El-Rashidy, AM Elhady… - Sensors, 2023 - mdpi.com
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 …

Quantifying Parkinson's disease motor severity under uncertainty using MDS-UPDRS videos

M Lu, Q Zhao, KL Poston, EV Sullivan… - Medical image …, 2021 - Elsevier
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 …

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 …

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 …

[HTML][HTML] Explainable classification of Parkinson's disease using deep learning trained on a large multi-center database of T1-weighted MRI datasets

M Camacho, M Wilms, P Mouches, H Almgren… - NeuroImage: Clinical, 2023 - Elsevier
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 …