Levodopa responsiveness in Parkinson’s disease: harnessing real-life experience with machine-learning analysis
Author:
Publisher
Springer Science and Business Media LLC
Subject
Biological Psychiatry,Psychiatry and Mental health,Neurology (clinical),Neurology
Link
https://link.springer.com/content/pdf/10.1007/s00702-022-02540-2.pdf
Reference39 articles.
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2. Arena JE, Cerquetti D, Rossi M, Chaves H, Rollan C, Dossi DE, Merello M (2016) Influence of white matter MRI hyper-intensities on acute L-dopa response in patients with Parkinson’s disease. Parkinsonism Relat Disord 24:126–128. https://doi.org/10.1016/j.parkreldis.2016.01.017
3. Armananzas R, Bielza C, Chaudhuri KR, Martinez-Martin P, Larranaga P (2013) Unveiling relevant non-motor Parkinson’s disease severity symptoms using a machine learning approach. Artif Intell Med 58:195–202. https://doi.org/10.1016/j.artmed.2013.04.002
4. Avisar H, Guardia-Laguarta C, Area-Gomez E, Surface M, Chan AK, Alcalay RN, Lerner B (2021) Lipidomics prediction of Parkinson’s disease severity: A machine-learning analysis. J Parkinsons Dis 11:1141–1155. https://doi.org/10.3233/JPD-202476
5. Avisar H, Guardia-Laguarta C, Surface M, Papagiannakis N, Maniati M, Antonellou R, Papadimitriou D, Koros C, Athanassiadou A, Przedborski S, Lerner B, Stefanis L, Area-Gomez E, Alcalay RN (2022) Lipid level alteration in human and cellular models of alpha synuclein mutations. NPJ Parkinsons Dis 8:52. https://doi.org/10.1038/s41531-022-00313-y
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1. Acute effect of levodopa on orthostatic hypotension and its association with motor responsiveness in Parkinson's disease: Results of acute levodopa challenge test;Parkinsonism & Related Disorders;2023-10
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