Abstract
Alzheimer's disease (AD) and other dementias have become the fifth leading cause of death worldwide. Accurate early detection of the disease and its precursor, Mild Cognitive Impairment (MCI), is crucial to alleviate the burden on the healthcare system. While most of the existing work in the literature applied neural networks directly together with several data pre-processing techniques, we proposed in this paper a screening system that is to perform classification based on automatic processing of the transcripts of speeches from the subjects undertaking a neuropsychological test. Our system is also shown applicable to different datasets and languages, suggesting that our system holds a high potential to be deployed widely in hospitals across regions. We conducted comprehensive experiments on two different languages datasets, the Pitt dataset and the NTUHV dataset, to validate our study. The results showed that our proposed system significantly outperformed the previous works on both datasets, with the score of the area under the receiver operating characteristic curve (AUROC) of classifying AD and healthy control (HC) being as high as 0.92 on the Pitt dataset and 0.97 on the NTUHV dataset. The performance on classifying MCI and HC remained promising, with the AUROC being 0.83 on the Pitt dataset and 0.88 on the NTUHV dataset.
Highlights
Alzheimer’s disease (AD) and other dementias have become the fifth leading cause of death worldwide
We evaluated our deep-learning model with a tenfold cross-validation process with five runs to obtain an area under the receiver operating characteristic curve (AUROC) of classifying AD and healthy control (HC) of 0.92 on the Pitt dataset and an AUROC of 0.97 on the NTUHV dataset
All metrics except AUROC are reported using a threshold of 0.5, i.e., Predicted probability larger than 50% would be classified as AD, whereas probability smaller than 50% would be deemed as HC
Summary
Alzheimer’s disease (AD) and other dementias have become the fifth leading cause of death worldwide. In the stage of MCI due to AD, mild cognitive declines can be observed and may be noticeable to family members. Such cognitive difficulties might not significantly impact individuals’ ability to handle everyday activities. In the stage of dementia due to AD, compared with normal age-related change, significant cognitive signs can be observed in patients with AD, including memory loss that disrupts daily life, the challenges in planning or solving problems, the disorientation to place or time information, having difficulty in completing familiar tasks at home, having trouble understanding complex instructions or spatial relationships, losing semantic knowledge[7].
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