Predicting the Stages of Dementia Using the Oasis Dataset
Keywords:
Dementia, Open Access Series of Imaging Studies (OASIS), Machine Learning (ML), deep learning (DL), Alzheimer’s disease, predictive modeling, neuroimaging, classification, early diagnosis, brain volume, cognitive testingAbstract
The research utilizes the OASIS dataset to predict various stages of dementia beginning from normal cognition and ending at advanced Alzheimer's disease. Neuroimaging data collected in the OASIS dataset provide suitable resources for model prediction using ML algorithms. Research methods based on DL operated on the provided dataset for dementia onset prediction. The important features for prediction included age along with gender and brain volume size and cognitive testing outcomes. Both training and testing sets of data were isolated for model performance evaluation in the provided dataset through the evaluation of accuracy together with precision and recall and F1-score metrics.
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