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A Step Towards the Automated Diagnosis of Parkinson's Disease: Analyzing Handwriting Movements.

, , , , , , and . CBMS, page 171-176. IEEE Computer Society, (2015)

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A survey on computer-assisted Parkinson's Disease diagnosis., , , , , and . Artif. Intell. Medicine, (2019)A new computer vision-based approach to aid the diagnosis of Parkinson's disease., , , , , , and . Comput. Methods Programs Biomed., (2016)Learning visual representations with optimum-path forest and its applications to Barrett's esophagus and adenocarcinoma diagnosis., , , , , , , , and . Neural Comput. Appl., 32 (3): 759-775 (2020)An Identification of Japanese Numerical Characters on a Biometrical Smart Pen System., , , , and . AutoID, page 232-237. IEEE, (2007)Handwritten dynamics assessment through convolutional neural networks: An application to Parkinson's disease identification., , , , , , and . Artif. Intell. Medicine, (2018)Hierarchical Learning Using Deep Optimum-Path Forest., , , , , and . CoRR, (2021)Parkinson Disease Identification Using Residual Networks and Optimum-Path Forest., , , , , , and . SACI, page 325-330. IEEE, (2018)New pen device for biometrical 3D pressure analysis of handwritten characters, words and signatures., , and . WBMA@MM, page 38-44. ACM, (2003)Deep Learning-Aided Parkinson's Disease Diagnosis from Handwritten Dynamics., , , , and . SIBGRAPI, page 340-346. IEEE Computer Society, (2016)A Step Towards the Automated Diagnosis of Parkinson's Disease: Analyzing Handwriting Movements., , , , , , and . CBMS, page 171-176. IEEE Computer Society, (2015)