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Machine learning approach for bipolar disorder analysis and recognition based on handwriting digital images | ||
| AUT Journal of Mathematics and Computing | ||
| مقالات آماده انتشار، پذیرفته شده، انتشار آنلاین از تاریخ 26 فروردین 1403 | ||
| نوع مقاله: Original Article | ||
| شناسه دیجیتال (DOI): 10.22060/ajmc.2024.22576.1176 | ||
| نویسندگان | ||
| Ahmadali Jamali* 1؛ Reza kargar2؛ Shahin Alipour3؛ Mohsen Rostami Malkhalife2 | ||
| 1Islamic Azad university of Science and research of Tehran, Iran | ||
| 2Islamic Azad University (IAU) - Islamic Azad University (IAU), Science and Research Branch, Iran | ||
| 3University of Houston, Department of Biomedical Engineering, 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: 331 |
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