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  • Deep Learning
  • NLP

Alzheimer's Disease Prediction

A diagnostic support system for early Alzheimer's disease detection using imaging and behavioral data.

Overview

Deep learning models classify Alzheimer's disease from brain MRI images and detect disease indicators in behavioural data. A built-in chatbot answers patient and caregiver questions about what the results mean.

Problem Statement

Alzheimer's is usually diagnosed once daily functioning has already declined, when intervention options have narrowed. Early markers exist in MRI scans and behavioural patterns, but reading them requires specialist time that most patients never get.

Proposed Solution

Combine imaging-based classification with behavioural pattern analysis for earlier detection, and attach a chatbot so patients and caregivers can understand the result without a second appointment.

Key Features

  • Deep Learning-Based Detection

    Predicts Alzheimer's disease from brain MRI images.

  • Behavioral Pattern Analysis

    Detects disease indicators from behavioral data.

  • Chatbot Query Resolution

    Answers patient/caregiver questions about results.

Technologies Used

Deep Learning

  • CNN
  • TensorFlow / Keras
  • Transfer learning
  • OpenCV

NLP

  • Chatbot intent handling
  • Transformers
  • Python

Application

  • Flask
  • SQLite
  • Bootstrap

Project Workflow

  1. 1

    Image upload

    A brain MRI scan is uploaded and preprocessed.

  2. 2

    Classification

    The CNN predicts disease stage or presence.

  3. 3

    Behavioural analysis

    Behavioural indicators are scored alongside imaging.

  4. 4

    Query resolution

    The chatbot explains the outcome to patient or caregiver.

What You'll Receive

  • Complete, runnable source code with folder structure
  • Project report and technical documentation
  • Ready-to-present PPT content
  • Setup and installation walkthrough
  • Line-by-line project explanation session
  • Viva question bank with answers
  • Bug fixing and troubleshooting help
  • Post-delivery support after submission

Frequently Asked Questions

How much does this project cost?

Every project is quoted individually, because the price depends on the modules you need, your technology stack, your college's format and your deadline. Send us the project name on WhatsApp and we'll share a quote the same day.

Can the project be customised to my college requirements?

Yes. Share your guide's requirements, preferred technology stack and abstract format, and we adapt the modules, dataset or UI accordingly.

Will I be able to explain this project during my viva?

That is the point of the explanation session. We walk you through the architecture, every module, the flow of data and the results, and hand over a viva question bank with answers.

What if the project does not run on my laptop?

We help you with setup end to end — dependencies, environment, database and configuration — over chat or a call until it runs on your machine.

Do I get support after submission?

Yes. Post-delivery support is included, so you can come back for fixes, doubts or demo help even after the project is delivered.

Want This Project?

Get complete source code, documentation, PPT, explanation, and support.

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