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Machine learning approach for bipolar disorder analysis and recognition based on handwriting digital images | ||
| AUT Journal of Mathematics and Computing | ||
| مقاله 4، دوره 6، شماره 3، مهر 2025، صفحه 223-239 اصل مقاله (1007.04 K) | ||
| نوع مقاله: Original Article | ||
| شناسه دیجیتال (DOI): 10.22060/ajmc.2024.22576.1176 | ||
| نویسندگان | ||
| Ahmadali Jamali* 1؛ Reza kargar1؛ Shahin Alipour2؛ Mohsen Rostamy-Malkhalifeh1 | ||
| 1Science and Research Branch, Islamic Azad University (IAU), Tehran, Iran | ||
| 2Department of Biomedical Engineering, University of Houston, USA | ||
| چکیده | ||
| In some cases, handwriting is a manifestation of the human mind, and it can reveal various psychological characteristics and mental disorders. Among these disorders, bipolar disorder is a well-known and widely studied condition in cognitive science and psychotherapy, and it can be detected in handwriting. In this research, we applied image processing techniques to analyze the handwriting characteristics of people with bipolar disorder based on their responses to a survey. We also proposed a machine learning model that can classify whether a person has bipolar disorder or not by using their handwriting as an input. | ||
| کلیدواژه‌ها | ||
| Bipolar disorder؛ Handwriting؛ Image processing؛ Machine learning | ||
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آمار تعداد مشاهده مقاله: 416 تعداد دریافت فایل اصل مقاله: 25 |
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