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A study on classification using machine learning for dementia evaluation

Umemura, Kanta, Kawanaka, Hiroharu, Hicks, Yulia, Setchi, Rossitza, Takamatsu, Daisuke and Tsuruoka, Shinji 2020. A study on classification using machine learning for dementia evaluation. Presented at: IEEE 2nd Global Conference on Life Sciences and Technologies (LifeTech 2020), Kyoto, Japan, 10-12 March 2020. 2020 IEEE 2nd Global Conference on Life Sciences and Technologies (LifeTech). IEEE, pp. 101-103. 10.1109/LifeTech48969.2020.1570619133

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Abstract

Recently, the number of dementia patients has been increasing due to the aging society. In Japan, a paper-based examination is the main-stream to measure the cognitive function of a subject, but these paper-based tests give much burden to not only patients but also evaluators like facility and medical staff. Therefore, it is necessary to develop a system that can automatically judge the degree of dementia progression, not to burden the doctor. Also, it is required to add play ability not to be a burden on the elderly. From this point of view, the authors developed a recreation game like a puzzle game. This system is easy to play for elderly people and is not a burden. Also, the question-answer is clear, so it is suitable for automatic judgment. We use the obtained features during recreation game to diagnose the degree of dementia progression. We committed the capability of machine learning techniques. Finally, we discussed that the collected features are sufficient to diagnose the degree of dementia progression.

Item Type: Conference or Workshop Item (Paper)
Date Type: Published Online
Status: Published
Schools: Engineering
Publisher: IEEE
ISBN: 9781728170633
Date of First Compliant Deposit: 1 October 2020
Date of Acceptance: 28 January 2020
Last Modified: 01 Oct 2020 15:40
URI: http://orca.cf.ac.uk/id/eprint/135083

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