Dementia Prediction Using Machine Learning

Dementia is a chronic and degenerative condition, which has become a major health concern among the elderly. With ever-continuing cases of dementia, it has become a very challenging task in the 21st century to provide care for patients with dementia. This paper proposes a framework for the prediction of dementia using the data collected from the OASIS (Open Access Series of Imaging Studies) project which was made available by the Washington University Alzheimer's Disease Research Centre. Different techniques have been implemented for data imputation, pre-processing and data transformation to create suitable data for training the model. Machine learning approaches like Adaboost (AB), Decision Tree (DT), Extra Tree (ET), Gradient Boost (GB), K-Nearest Neighbour (KNN), Logistic Regression (LR), Naïve Bayes (NB),…