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- Title
Machine Learning for Dementia Prediction: A Systematic Review and Future Research Directions.
- Authors
Javeed, Ashir; Dallora, Ana Luiza; Berglund, Johan Sanmartin; Ali, Arif; Ali, Liaqat; Anderberg, Peter
- Abstract
Nowadays, Artificial Intelligence (AI) and machine learning (ML) have successfully provided automated solutions to numerous real-world problems. Healthcare is one of the most important research areas for ML researchers, with the aim of developing automated disease prediction systems. One of the disease detection problems that AI and ML researchers have focused on is dementia detection using ML methods. Numerous automated diagnostic systems based on ML techniques for early prediction of dementia have been proposed in the literature. Few systematic literature reviews (SLR) have been conducted for dementia prediction based on ML techniques in the past. However, these SLR focused on a single type of data modality for the detection of dementia. Hence, the purpose of this study is to conduct a comprehensive evaluation of ML-based automated diagnostic systems considering different types of data modalities such as images, clinical-features, and voice data. We collected the research articles from 2011 to 2022 using the keywords dementia, machine learning, feature selection, data modalities, and automated diagnostic systems. The selected articles were critically analyzed and discussed. It was observed that image data driven ML models yields promising results in terms of dementia prediction compared to other data modalities, i.e., clinical feature-based data and voice data. Furthermore, this SLR highlighted the limitations of the previously proposed automated methods for dementia and presented future directions to overcome these limitations.
- Subjects
DIAGNOSIS of dementia; DIAGNOSTIC imaging; DESCRIPTIVE statistics; SYSTEMATIC reviews; MEDLINE; COMPUTER-aided diagnosis; DEEP learning; AGING; MACHINE learning; AUTOMATION; DEMENTIA; EARLY diagnosis; ONLINE information services; DISEASE progression; SYMPTOMS
- Publication
Journal of Medical Systems, 2023, Vol 47, Issue 1, p1
- ISSN
0148-5598
- Publication type
Article
- DOI
10.1007/s10916-023-01906-7