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Analyze WZT Images to Predict the Type of Depression and Dementia in the Elderly Using Deep Learning
- Kim, Kyung-Yeul;
- Yang, Young-Bo;
- Kim, Mi-Ra;
- Park, Ji Su;
- Kim, Jihie
Citations
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0초록
Analyzing depression and dementia in the elderly using deep learning based on drawing images created by the elderly in the Wartegg-Zeichentest (WZT) is limited. This study utilized drawing data expressed through the WZT test and employed deep learning to predict depression and dementia in the elderly. The analysis of geriatric diseases using Deep Learning necessitates further information gathering and related research on diseases, with the expectation of creating numerous opportunities in various fields of deep learning. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.
키워드
Convolution Neural Network; deep learning; depression and dementia; prediction; Wartegg-Zeichentest
- 제목
- Analyze WZT Images to Predict the Type of Depression and Dementia in the Elderly Using Deep Learning
- 저자
- Kim, Kyung-Yeul; Yang, Young-Bo; Kim, Mi-Ra; Park, Ji Su; Kim, Jihie
- 발행일
- 2024-09
- 유형
- Conference Paper
- 권
- 1190
- 페이지
- 325 ~ 329