Feature Relevance Analysis for Handwriting Based Identification of Parkinson’s Disease
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Publisher
Springer International Publishing
Link
https://link.springer.com/content/pdf/10.1007/978-3-031-04112-9_12
Reference30 articles.
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3. Jeancolas, L., et al.: X-vectors: new quantitative biomarkers for early Parkinson’s disease detection from speech. Front. Neuroinform. 15, 4 (2021)
4. Karaman, O., Çakın, H., Alhudhaif, A., Polat, K.: Robust automated parkinson disease detection based on voice signals with transfer learning. Expert Syst. Appl. 178, 115013 (2021)
5. Drotár, P., Mekyska, J., Rektorová, I., Masarová, L., Smékal, Z., Faundez-Zanuy, M.: Analysis of in-air movement in handwriting: a novel marker for Parkinson’s disease. Comput. Meth. Progr. Biomed. 117(3), 405–411, 115013 (2014)
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