Machine learning for large‐scale wearable sensor data in Parkinson's disease: Concepts, promises, pitfalls, and futures

KJ Kubota, JA Chen, MA Little - Movement disorders, 2016 - Wiley Online Library
For the treatment and monitoring of Parkinson's disease (PD) to be scientific, a key
requirement is that measurement of disease stages and severity is quantitative, reliable, and …

Closing the loop for patients with Parkinson disease: where are we?

H Teymourian, F Tehrani, K Longardner… - Nature Reviews …, 2022 - nature.com
Although levodopa remains the most efficacious symptomatic therapy for Parkinson disease
(PD), management of levodopa treatment during the advanced stages of the disease is …

[HTML][HTML] Efficient RT-QuIC seeding activity for α-synuclein in olfactory mucosa samples of patients with Parkinson's disease and multiple system atrophy

CMG De Luca, AE Elia, SM Portaleone… - Translational …, 2019 - Springer
Background Parkinson's disease (PD) is a neurodegenerative disorder whose diagnosis is
often challenging because symptoms may overlap with neurodegenerative parkinsonisms …

Developing and validating Parkinson's disease subtypes and their motor and cognitive progression

M Lawton, Y Ben-Shlomo, MT May, F Baig… - Journal of Neurology …, 2018 - jnnp.bmj.com
Objectives To use a data-driven approach to determine the existence and natural history of
subtypes of Parkinson's disease (PD) using two large independent cohorts of patients newly …

[HTML][HTML] Data-driven subtyping of Parkinson's disease using longitudinal clinical records: a cohort study

X Zhang, J Chou, J Liang, C Xiao, Y Zhao, H Sarva… - Scientific reports, 2019 - nature.com
Parkinson's disease (PD) is associated with diverse clinical manifestations including motor
and non-motor signs and symptoms, and emerging biomarkers. We aimed to reveal the …

An rnn architecture with dynamic temporal matching for personalized predictions of parkinson's disease

C Che, C Xiao, J Liang, B Jin, J Zho, F Wang - Proceedings of the 2017 SIAM …, 2017 - SIAM
Parkinson's disease (PD) is a chronic disease that develops over years and varies
dramatically in its clinical manifestations. A preferred strategy to resolve this heterogeneity …

[HTML][HTML] The Personalized Parkinson Project: examining disease progression through broad biomarkers in early Parkinson's disease

BR Bloem, WJ Marks, AL Silva de Lima, ML Kuijf… - BMC neurology, 2019 - Springer
Background Our understanding of the etiology, pathophysiology, phenotypic diversity, and
progression of Parkinson's disease has stagnated. Consequently, patients do not receive …

[HTML][HTML] Discovery of Parkinson's disease states and disease progression modelling: a longitudinal data study using machine learning

KA Severson, LM Chahine, LA Smolensky… - The Lancet Digital …, 2021 - thelancet.com
Background Parkinson's disease is heterogeneous in symptom presentation and
progression. Increased understanding of both aspects can enable better patient …

Finding useful biomarkers for Parkinson's disease

AS Chen-Plotkin, R Albin, R Alcalay… - Science translational …, 2018 - science.org
Finding useful biomarkers for Parkinson’s disease | Science Translational Medicine news
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Smartphone motor testing to distinguish idiopathic REM sleep behavior disorder, controls, and PD

S Arora, F Baig, C Lo, TR Barber, MA Lawton, A Zhan… - Neurology, 2018 - AAN Enterprises
Objective We sought to identify motor features that would allow the delineation of individuals
with sleep study-confirmed idiopathic REM sleep behavior disorder (iRBD) from controls and …