Xuechao Wang

PointExplainer : towards transparent Parkinson’s disease diagnosis

Xuechao Wang, Sven Nõmm, Junqing Huang (UGent) , Kadri Medijainen, Aaro Toomela and Michael Ruzhansky (UGent)

(2026) INFORMATION FUSION. 129.

Performing particle image segmentation on an extremely small dataset

Marianna Chatzakou (UGent) , Junqing Huang (UGent) , Bogdan Parakhonskiy (UGent) , Michael Ruzhansky (UGent) , Andre Skirtach (UGent) , Junnan Song (UGent) and Xuechao Wang

(2024) Extended Abstracts 2021/2022 : Ghent analysis and PDE seminar. In Trends in Mathematics 2. p.295-304

Add to list

Text matching as time series matching

Xuechao Wang

(2024) Extended Abstracts 2021/2022 : Ghent analysis and PDE seminar. In Trends in mathematics (TM) 2. p.283-293

Add to list

An efficient neural network for the diagnosis of Parkinson’s disease using dynamic handwriting analysis

Xuechao Wang, Sven Nõmm, Junqing Huang (UGent) , Marianna Chatzakou (UGent) and Michael Ruzhansky (UGent)

(2024) EXTENDED ABSTRACTS MWCAPDE 2023. In Trends in mathematics (TM) 1. p.97-104

Add to list

Journal Article
A1
open access

LSTM-CNN : an efficient diagnostic network for Parkinson's disease utilizing dynamic handwriting analysis

Xuechao Wang, Junqing Huang (UGent) , Marianna Chatzakou (UGent) , Kadri Medijainen, Aaro Toomela, Sven Nomm and Michael Ruzhansky (UGent)

(2024) COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE. 247. p.1-9

Add to list

Journal Article
A1
open access

Comparison of one- two- and three-dimensional CNN models for drawing-test-based diagnostics of the Parkinson’s disease

Xuechao Wang, Junqing Huang (UGent) , Marianna Chatzakou (UGent) , Sven Nõmm, Elli Valla, Kadri Medijainen, Pille Taba, Aaro Toomela and Michael Ruzhansky (UGent)

(2024) BIOMEDICAL SIGNAL PROCESSING AND CONTROL. 87(Part B).

Add to list

Conference Paper
P1
open access

A light-weight CNN model for efficient Parkinson's disease diagnostics

Xuechao Wang, Junqing Huang (UGent) , Marianna Chatzakou (UGent) , Kadri Medijainen, Pille Taba, Aaro Toomela, Sven Nomm and Michael Ruzhansky (UGent)

(2023) Computer-Based Medical Systems, 36th IEEE International symposium, Proceedings. In IEEE International Symposium on Computer-Based Medical Systems p.616-621

Add to list

Journal Article
A1
open access

Semi-sparsity for smoothing filters

Junqing Huang (UGent) , Haihui Wang, Xuechao Wang and Michael Ruzhansky (UGent)

(2023) IEEE TRANSACTIONS ON IMAGE PROCESSING. 32. p.1627-1639

Academic Bibliography

Xuechao Wang

PointExplainer : towards transparent Parkinson’s disease diagnosis

Performing particle image segmentation on an extremely small dataset

Text matching as time series matching

An efficient neural network for the diagnosis of Parkinson’s disease using dynamic handwriting analysis

LSTM-CNN : an efficient diagnostic network for Parkinson's disease utilizing dynamic handwriting analysis

Comparison of one- two- and three-dimensional CNN models for drawing-test-based diagnostics of the Parkinson’s disease

A light-weight CNN model for efficient Parkinson's disease diagnostics

Semi-sparsity for smoothing filters

Contents

Support

Contact