Catch Alzheimer's earlier, from a single MRI scan.
NeuroScan AI is a deep learning system that analyses brain MRI images to detect Alzheimer's disease in its early stages — giving doctors a fast, reliable second opinion when it matters most.
Refer for clinical review
Dementia is rising fast. Alzheimer's is behind most of it.
Diagnosing Alzheimer's early is hard, slow and depends on specialist expertise that many patients can't easily reach.
people were living with dementia worldwide in 2021.
new cases of dementia every year.
of dementia cases may be caused by Alzheimer's disease.
leading cause of death in the world is dementia.
global cost of dementia in 2019.
The brain changes before the symptoms are obvious.
Alzheimer's develops gradually. MRI can reveal structural changes in the brain, and spotting them early gives patients and families more time to plan, treat and adapt.
NeuroScan AI is designed to find those signals in routine MRI scans — quickly and consistently.
NeuroScan AI looks here
From MRI scan to decision support in four steps.
- 1
Upload the MRI
A standard brain MRI image is provided by the clinic or hospital.
- 2
Prepare the image
The scan is formatted for the deep learning model.
- 3
Deep learning analysis
A CNN built on MobileNet with transfer learning examines the brain image.
- 4
Support the doctor
A clear result — Alzheimer's or not — helps the clinician decide the next step.
Powerful accuracy from a lightweight model.
NeuroScan AI combines three ideas from deep learning to deliver high accuracy without heavy hardware.
Convolutional Neural Network
A CNN learns the visual patterns in brain MRI images that distinguish Alzheimer's from healthy scans.
Transfer learning
Starts from a model already pre-trained on general images, then adapts it to brain MRI — learning faster from less data.
MobileNet
An efficient network architecture designed to run with low computational complexity and memory use.
Near-perfect detection of Alzheimer's in MRI.
The MobileNet-based model reached a 99.86% accuracy rate in classifying brain MRI images as Alzheimer's or not.
Efficient by design
High accuracy while keeping computational complexity and memory cost low.
Suited to real-time monitoring
Fast enough to support ongoing, eco-friendly tracking of disease progression.
Source: Othman, Jawad & Jasim, Journal of Intelligent Systems and Internet of Things 16(2), 202–213 (2025). doi:10.54216/JISIoT.160215
Built to support the people who diagnose.
Neurologists
A fast second opinion on MRI scans during assessment.
Radiologists
Help prioritise scans that show signs of Alzheimer's.
Memory clinics
Support earlier diagnosis and planning for patients and families.
Hospitals
A lightweight tool that runs without expensive computing infrastructure.
A tool for doctors, not a replacement.
- Every result is decision support; diagnosis remains with the clinician.
- The current model performs binary classification: Alzheimer's or not.
- Research results come from benchmark MRI data; clinical validation in hospitals is the next step.
Where the research goes from here.
- Adding more pre-trained models to compare and combine.
- Expanding the dataset through data augmentation.
- MRI segmentation to isolate the key features of Alzheimer's.
Computer science and medical technology, side by side.
NeuroScan AI was founded in 2025 by a research team combining artificial intelligence with expertise in medical imaging and health technology.
Computer Science
Builds and trains the deep learning model and the diagnosis application.
Health & Medical Technologies
Brings knowledge of MRI imaging and clinical workflows, so results fit real diagnostic practice.
Frequently asked questions
What does NeuroScan AI do?
It analyses brain MRI images with deep learning to detect signs of Alzheimer's disease early, supporting doctors in their diagnosis.
How accurate is it?
The underlying MobileNet-based model achieved 99.86% accuracy in classifying MRI images, as published in the Journal of Intelligent Systems and Internet of Things (2025).
Does it replace a doctor's diagnosis?
No. NeuroScan AI is a decision-support tool. Diagnosis and treatment decisions always remain with qualified clinicians.
Why use MobileNet?
MobileNet is a lightweight network that keeps computing and memory costs low, which helps reduce overfitting and makes real-time use practical without expensive hardware.
What kind of scans does it use?
Magnetic Resonance Imaging (MRI) scans of the brain — a standard imaging test already used in Alzheimer's assessment.
Grounded in peer-reviewed research.
Read the study behind NeuroScan AI's deep learning approach to Alzheimer's detection.
Othman, O., Jawad, M. Q., & Jasim, O. M. (2025). Alzheimer detection using deep learning methods. Journal of Intelligent Systems and Internet of Things, 16(2), 202–213.
https://doi.org/10.54216/JISIoT.160215