Alzheimer’s Disease Classification using Machine Learning
Alzheimer disease is a neurological disorder for this disease there is no specific treatment. The classification of Alzheimer disease using deep learning methods will gave promising results and combination of high accuracy, short processing time. Early detection of Alzheimer disease can help patients received correct care. In this study, we developed a system of Alzheimer disease detection using Convolutional Neural Network (CNN) architecture using magnetic resonance imaging (MRI) scans images which are trained using Kaggle dataset. The Convolutional Neural Network (CNN) architecture gives the highest accuracy. Model is integrated with software interface developed using Tkinter.
In this project User have to provide input image from dataset folder according to input, model will classify the type of Alzheimer Disease:-
1. Mild Demented
2. Moderate Demented
3. Non Demented
4. Very mild Demented Model is integrated with software interface developed using Tkinter.
Alzheimer’s Disease Classification using Image Processing
Software Requirements :-
- Coding Language : Python
- Implementation: Software Framework.
- Operating system : Windows 10 / 11.
- Graphical User Interface : Tkinter
Hardware Requirement:-
- Input Devices : Keyboard, Mouse.
- System : Pentium i3 Processor.
- Hard Disk : 500 GB.
- RAM : 4 GB.
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