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The Early Detection of Dementia Disease Using Machine Learning Approach

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dc.contributor.author Kabir, Md Shariar
dc.contributor.author Khanom, Jakia
dc.contributor.author Bhuiyan, Md. Atik
dc.contributor.author Tumpa, Zerin Nasrin
dc.contributor.author Rabby, Sk. Fazlee
dc.contributor.author Bilgaiyan, Saurabh
dc.date.accessioned 2024-09-01T09:54:19Z
dc.date.available 2024-09-01T09:54:19Z
dc.date.issued 2023-05-24
dc.identifier.uri http://dspace.daffodilvarsity.edu.bd:8080/handle/123456789/13320
dc.description.abstract Early dementia detection is a crucial but challenging task in Bangladesh. Often, dementia is not recognized until it is too late to receive effective care. This results in part from a lack of knowledge about the illness and its signs and symptoms. Recent improvements in machine learning algorithms, however, may change this. In a recent study, we developed a model that can identify early dementia in Bangladesh using machine learning algorithms. This research paper proposed an efficient machine learning-based approach for early detection of dementia disease A dataset of 199 people with dementia and 175 healthy controls was used to develop the model. In 96% of the cases, the algorithm correctly identified dementia. This is a significant accomplishment that could revolutionize Bangladesh's dementia detection process. For patients to get the care they require, early dementia detection is essential. This study offers a proof-of-concept for the use of machine learning in dementia early detection & The results of this study suggest that machine learning models can be used as a powerful tool for early detection of dementia. en_US
dc.language.iso en_US en_US
dc.publisher IEEE en_US
dc.subject Dementia disease en_US
dc.subject Machine learning en_US
dc.title The Early Detection of Dementia Disease Using Machine Learning Approach en_US
dc.type Article en_US


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