{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,29]],"date-time":"2026-05-29T11:18:19Z","timestamp":1780053499629,"version":"3.54.0"},"reference-count":28,"publisher":"MDPI AG","issue":"4","license":[{"start":{"date-parts":[[2024,4,13]],"date-time":"2024-04-13T00:00:00Z","timestamp":1712966400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Information"],"abstract":"<jats:p>Parkinson\u2019s disease (PD) is a chronic brain disorder affecting millions worldwide. It occurs when brain cells that produce dopamine, a chemical controlling movement, die or become damaged. This leads to PD, which causes problems with movement, balance, and posture. Early detection is crucial to slow its progression and improve the quality of life for PD patients. This paper proposes a handwriting-based prediction approach combining a cosine annealing scheduler with deep transfer learning. It utilizes the NIATS dataset, which contains handwriting samples from individuals with and without PD, to evaluate six different models: VGG16, VGG19, ResNet18, ResNet50, ResNet101, and Vit. This paper compares the performance of these models based on three metrics: accuracy, precision, and F1 score. The results showed that the VGG19 model, combined with the proposed method, achieved the highest average accuracy of 96.67%.<\/jats:p>","DOI":"10.3390\/info15040220","type":"journal-article","created":{"date-parts":[[2024,4,15]],"date-time":"2024-04-15T03:56:13Z","timestamp":1713153373000},"page":"220","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":33,"title":["Early Parkinson\u2019s Disease Diagnosis through Hand-Drawn Spiral and Wave Analysis Using Deep Learning Techniques"],"prefix":"10.3390","volume":"15","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-9902-9636","authenticated-orcid":false,"given":"Yingcong","family":"Huang","sequence":"first","affiliation":[{"name":"School of Computer Science, Faculty of Engineering and Information Technology, University of Technology Sydney, Sydney, NSW 2007, Australia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kunal","family":"Chaturvedi","sequence":"additional","affiliation":[{"name":"School of Computer Science, Faculty of Engineering and Information Technology, University of Technology Sydney, Sydney, NSW 2007, Australia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7846-3249","authenticated-orcid":false,"given":"Al-Akhir","family":"Nayan","sequence":"additional","affiliation":[{"name":"Department of Computer Engineering, Chulalongkorn University, Bangkok 10330, Thailand"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7877-0804","authenticated-orcid":false,"given":"Mohammad Hesam","family":"Hesamian","sequence":"additional","affiliation":[{"name":"School of Computer Science, Faculty of Engineering and Information Technology, University of Technology Sydney, Sydney, NSW 2007, Australia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ali","family":"Braytee","sequence":"additional","affiliation":[{"name":"School of Computer Science, Faculty of Engineering and Information Technology, University of Technology Sydney, Sydney, NSW 2007, Australia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7745-9667","authenticated-orcid":false,"given":"Mukesh","family":"Prasad","sequence":"additional","affiliation":[{"name":"School of Computer Science, Faculty of Engineering and Information Technology, University of Technology Sydney, Sydney, NSW 2007, Australia"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2024,4,13]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"1591","DOI":"10.1002\/mds.26424","article-title":"MDS Clinical Diagnostic Criteria for Parkinson\u2019s Disease","volume":"30","author":"Postuma","year":"2015","journal-title":"Mov. 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