•  
  •  
 

Corresponding Author

Dilena Majid Bajalan

Authors ORCID

Dilena Majid Bajalan: https://orcid.org/0009-0009-5842-3595

Muayad Sadik Croock: https://orcid.org/0000-0001-5269-0697

Document Type

Article

Keywords

Alzheimer disease, CNN, AI, Mobile application, Alzheimer's life management, Kaggle, Deep learning in healthcare, MRI classification

Abstract

The defining feature of Alzheimer's disease (AD) is a gradual decline in symptoms over several years. This decline reduces the effectiveness of daily routines and leads to memory loss. Among the challenges posed by memory loss are difficulties in remembering names, faces, locations, and other important details. This study introduces an intelligent mobile application designed to assist in managing a patient's daily life, with an emphasis on routine activities and monitoring episodes of memory loss. Additionally, the application aims to detect Alzheimer's disease (AD) using a proposed deep learning model. The suggested Convolutional Neural Network (CNN) deep learning model is trained on a dataset of 11000 magnetic resonance imaging MRI scan images from Kaggle opensource website and has achieved 98% accuracy in detecting Alzheimer's from MRI scans. This application demonstrates effective performance in the realm of AD's detection, patient life management and reducing the financial strain on the relatives of patients.

Download

Share

COinS