Project Title: Evaluation of Machine Learning Algorithms for Early Detection of Alzheimer’s Disease (AD)

Project description: Implementation of machine learning algorithms to evaluate and develop a GUI prediction model across OASIS MRI data set with Boruta features selection algorithm based on the supervised machine learning method. The proposed methodologies included pre- processing, feature selection, EDA and machine learning algorithms on the detection of physical variations in brain accompaniments clinical valuation for early detection of AD.

Dataset: MRI related data that was generated by the Open Access Series of Imaging Studies (OASIS) project that is available on Kaggle and OASIS utilized for the purpose of training various machine learning models to identify patients with dementia or healthy status (binary classification).

Proposed prediction GUI (): FYP GUI & GUI Version 1