Analyzing MRI Scans to Detect Different Levels of Alzheimer’s Disease

Alzheimer’s disease is a progressive neurological disorder that affects millions of people, yet many individuals and caregivers struggle to interpret MRI scans and understand its severity without medical expertise. This lack of accessibility can delay early intervention and treatment. To address this issue, my project aims to develop an app that scans MRI images of the brain and determines the severity level of Alzheimer’s. By providing clear, easy-to-understand analysis, the app will help users recognize potential concerns and encourage timely medical consultation.

To develop the app, MRI images of the brain will be collected from publicly available datasets containing scans labeled with different stages of Alzheimer’s. A machine learning model will be trained to analyze these images and classify the severity level of the disease. The model will be integrated into a user-friendly mobile or web application, allowing users to upload MRI scans for analysis. The app will then process the image, compare it to trained data, and provide a severity assessment along with an easy-to-understand explanation. Testing will be conducted using additional MRI scans to evaluate the model’s accuracy, and adjustments will be made as needed to improve performance.

The accuracy of the app’s severity assessments will be evaluated by comparing its results to the known classifications of MRI scans from the dataset. If the model consistently classifies the severity of Alzheimer’s correctly, it suggests that the app can be a useful tool for identifying potential concerns. Any inconsistencies in the results will be examined to determine areas for improvement, such as refining the training dataset or adjusting the model’s parameters. Additionally, the app’s usability will be assessed to ensure that the information is presented in a clear and understandable way. By analyzing accuracy rates and user experience, the project will determine the app’s potential effectiveness in helping individuals recognize signs of Alzheimer’s.

This project demonstrates the potential of using machine learning to analyze MRI scans and assess the severity of Alzheimer’s in an accessible way. By developing an app that can classify the severity level of the disease, the goal is to help individuals better understand MRI results and recognize possible concerns early on. While further improvements may be needed to enhance accuracy and reliability, the app serves as a step toward making medical imaging more understandable for non-experts. With continued development, this technology could contribute to raising awareness and encouraging earlier medical consultation, ultimately supporting better management of Alzheimer’s disease.

Website (Alzheimer’s Association)

Alzheimer’s Association. “What Is Alzheimer’s?” Alzheimer's Association, 2024, https://www.alz.org/alzheimers-dementia/what-is-alzheimers. Accessed 19 Mar. 2025.

Dataset (Mendeley Data)

Feng, Chuanlei, et al. "MRI Image Dataset for Alzheimer’s Disease Stages." Mendeley Data, vol. 2, 2023, https://data.mendeley.com/datasets/kcjt4v658x/2. Accessed 19 Mar. 2025.

I would like to acknowledge Lynn Gordon For helping me grasp a deeper understanding for alzhimers disease, and Cathal for working with me and helping me gain a deeper understanding of my code.