Comparison of CNN-Learned vs. Handcrafted Features for Detection of Parkinson's Disease Dysgraphia in a Multilingual Dataset

Comparison of CNN-Learned vs. Handcrafted Features for Detection of Parkinson's Disease Dysgraphia in a Multilingual Dataset

Parkinson's disease dysgraphia (PDYS), one of the earliest signs of Parkinson's disease (PD), has been researched as a promising biomarker of PD and as the target of a noninvasive and inexpensive approach to monitoring the progress of the disease. However, although several approaches to su...

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Bibliographic Details
Main Authors: Zoltan Galaz, Peter Drotar, Jiri Mekyska, Matej Gazda, Jan Mucha, Vojtech Zvoncak, Zdenek Smekal, Marcos Faundez-Zanuy, Reinel Castrillon, Juan Rafael Orozco-Arroyave, Steven Rapcsak, Tamas Kincses, Lubos Brabenec, Irena Rektorova
Format: Article
Language:English
Published: Frontiers Media S.A. 2022-05-01
Series:Frontiers in Neuroinformatics
Subjects:
machine learning
deep learning
feature extraction
Parkinson's disease dysgraphia
handwriting analysis
Online Access:https://www.frontiersin.org/articles/10.3389/fninf.2022.877139/full

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https://www.frontiersin.org/articles/10.3389/fninf.2022.877139/full

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