DETECTION OF ALZHEIMER’S DISEASE AND ASSISTANCE
Abstract
As the world is experiencing population growth, the portion of older people aged 65 and above is also growing. As a result, dementia with Alzheimer’s disease is expected to increase rapidly in the next few years. Currently, healthcare systems require accurate detection of the disease for its treatment and prevention. Therefore, it has become essential to develop a framework for the detection of Alzheimer’s disease to avoid complications. To this end, a novel framework based on deep learning (DL) methods is proposed to detect Alzheimer’s disease. The raw data from MRI scans are pre-processed, before applying a deep learning approach. Another feature of our system is to assist Alzheimer’s patients and their caregivers to provide support, like guidelines on how to handle them when they go through psychological depression, anger issues, etc., and how a person should behave with an Alzheimer’s patient. Therefore, our
system will be very effective and usable for patients and their relatives as well as caregivers. It can also provide insight into the disease, different stages, causes, symptoms, and related matters.
Keywords:
ResNet, DenseNet, LSTM, Deep LearningPublished
Issue
Section
License
Copyright (c) 2023 International Journal on Emerging Research Areas

This work is licensed under a Creative Commons Attribution 4.0 International License.
All published work in this journal is licensed under the Creative Commons Attribution 4.0 International License (CC BY 4.0). This license permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
How to Cite
Similar Articles
- Albin Thomas Lalu, Resmara S, Alen A Thankachen, Sneha Priya Sebastian, Dany Jennez , Lirin Blesson, Kesia Sunny, Fault Detection of Transmission Lines Using Unmanned Aerial Vehicle (UAV) , International Journal on Emerging Research Areas: Vol. 3 No. 1 (2023): IJERA
- George P Kurias, Gokul Krishna AU, Jifith Joseph, Sharunmon R, Linsa Mathew, A Review of Methodologies for Detecting Missing and Wanted People Using Machine Learning and Video Surveillance , International Journal on Emerging Research Areas: Vol. 4 No. 2 (2024): IJERA
- Joel Lee George, Karthik S Kumar , Riya Merce Thomas, Roshan Roy Varghese, Simy Mary Kurian, Epidemo A Machine Learning Regression-Based , International Journal on Emerging Research Areas: Vol. 4 No. 1 (2024): IJERA
- Ansamol Varghese, Anoushkha Tresa, Athira John, Ignatious Ealias Roy, M S Gautham Sankar, A Machine Learning Approach to Fake News Detection , International Journal on Emerging Research Areas: Vol. 3 No. 1 (2023): IJERA
- Adithya Satheesh, Ashwin S Nair, Darren Padamittam Jacob, Athul Rajeev, Er. Maheshwary Sreenath, Intrusion Countermeasure System , International Journal on Emerging Research Areas: Vol. 4 No. 1 (2024): IJERA
- Adithya Satheesh, Ashwin S Nair, Darren Padamittam Jacob, Athul Rajeev, Er. Maheshwary Sreenath, Intrusion Countermeasure System , International Journal on Emerging Research Areas: Vol. 4 No. 1 (2024): IJERA
- Tom Kurian, Ektha P S, Chethana Raj T, Diona Joseph, Annu Mary Abraham, Intelligent Disease Prediction in Hydroponic Systems Using Machine Learning , International Journal on Emerging Research Areas: Vol. 4 No. 1 (2024): IJERA
- Layana S Pradeep, Milen Ninan Ittiyeipe, Shahina S, Soumya A S, Ojus Thomas Lee , Gayathri Mohan, A REVIEW OF LOAD ESTIMATION AND DISTRIBUTION STRATEGY FOR RENEWABLE ENERGY SOURCES , International Journal on Emerging Research Areas: Vol. 4 No. 1 (2024): IJERA
- Fabeela Ali Rawther, Raihana Rasaldeen, Stefi Marshal Fernandez, Irin Rose Jaison, Ria Mariam Mathews, A Survey on Automating Answer-Sheet Evaluation Using AI Techniques , International Journal on Emerging Research Areas: Vol. 4 No. 2 (2024): IJERA
- Honey Thomas, Linna Benny, Saya Nezrin, Navya Neethi S, Niya Joseph, Smart Communication Software for the Hearing Impaired Using Artificial Intelligence , International Journal on Emerging Research Areas: Vol. 4 No. 2 (2024): IJERA
You may also start an advanced similarity search for this article.