Comparison of one- two- and three-dimensional CNN models for drawing-test-based diagnostics of the Parkinson’s diseaseWang, Xuechao; Huang, Junqing; Chatzakou, Marianna; Nõmm, Sven; Valla, Elli; Medijainen, Kadri; Taba, Pille; Toomela, Aaro; Ruzhansky, MichaelBiomedical signal processing and control2024 / art. 105436, 8 p https://doi.org/10.1016/j.bspc.2023.105436 An efficient neural network for the diagnosis of Parkinson’s disease using dynamic handwriting analysisWang, Xuechao; Nõmm, Sven; Huang, Junqing; Chatzakou, Marianna; Ruzhansky, MichaelExtended Abstracts MWCAPDE 2023 : Methusalem Workshop on Classical Analysis and Partial Differential Equations2024 / p. 97 - 104 https://doi.org/10.1007/978-3-031-41665-1_11 Article Collection metrics at Scopus Article at Scopus Article at WOS A light-weight CNN model for efficient Parkinsons disease diagnosticsWang, Xuechao; Huang, Junqing; Chatzakou, Marianna; Medijainen, Kadri; Taba, Pille; Toomela, Aaro; Nõmm, Sven; Ruzhansky, Michael36th IEEE International Symposium on Computer-Based Medical Systems, CBMS 2023, Aquila, 22-24 June 20232023 / p. 616-621 https://doi.org/10.1109/CBMS58004.2023.00289 Conference proceedings at Scopus Article at Scopus Article at WOS LSTM-CNN : an efficient diagnostic network for Parkinson's disease utilizing dynamic handwriting analysisWang, Xuechao; Huang, Junqing; Chatzakou, Marianna; Medijainen, Kadri; Toomela, Aaro; Nõmm, Sven; Ruzhansky, MichaelComputer Methods and Programs in Biomedicine2024 / art. 108066 https://doi.org/10.1016/j.cmpb.2024.108066 Journal metrics at Scopus Article at Scopus Journal metrics at WOS Article at WOS