Longitudinal clustering analysis and prediction of Parkinson's disease progression using radiomics and hybrid machine learning

We employed machine learning approaches to (I) determine distinct progression trajectories in Parkinson's disease (PD) (unsupervised clustering task), and (II) predict progression trajectories (supervised prediction task), from early (years 0 and 1) data, making use of clinical and imaging feat...

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Vydané v:	Quantitative imaging in medicine and surgery Ročník 12; číslo 2; s. 906
Hlavní autori:	Salmanpour, Mohammad R, Shamsaei, Mojtaba, Hajianfar, Ghasem, Soltanian-Zadeh, Hamid, Rahmim, Arman
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	China 01.02.2022
Predmet:	outcome prediction Parkinson’s disease (PD) hybrid machine learning methods longitudinal clustering
ISSN:	2223-4292
On-line prístup:	Zistit podrobnosti o prístupe
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