Scopus Indexed Publications

Paper Details


Title
The Early Detection of Dementia Disease Using Machine Learning Approach
Author
Md Shariar Kabir, Jakia Khanom, Md. Atik Bhuiyan , Mr. SK. Fazlee Rabby, Ms. Zerin Nasrin Tumpa,
Email
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.

Keywords
"Dementia , Machine Learning , Prediction , Accuracy"
Journal or Conference Name
2023 International Conference on Computer Communication and Informatics, ICCCI 2023
Publication Year
2023
Indexing
scopus