Alzheimer's Disease Detection using Machine Learning | 2024 Machine Learning Project
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🔥 Our Proposed Project Title: Early detection of Alzheimer's Disease using Mobilenet Algorithm: A Deep Learning Approach
🔍Implementation: Flask.
🧠Algorithm / Model Used: MobileNet Algorithm
🎯Web Framework: Flask.
💻Frontend: HTML, CSS, JavaScript.
ABSTRACT
Alzheimer’s disease (AD) is a progressive neurodegenerative disorder that significantly impacts cognitive function, memory, and daily living. Early detection of AD is critical for timely intervention and improving the quality of life for patients. This project proposes an innovative approach to Alzheimer’s disease prediction using the MobileNet algorithm, a lightweight and efficient deep learning architecture. The MobileNet model is trained on medical imaging datasets, such as MRI or CT scans, to classify and predict Alzheimer’s disease at its early stages.
The proposed system leverages the computational efficiency of MobileNet to ensure scalability and accessibility, making it suitable for deployment on resource-constrained devices like smartphones or embedded systems. The model undergoes rigorous preprocessing and training to achieve high accuracy, robustness, and generalizability. Performance evaluation is conducted using metrics such as accuracy, precision, recall, and F1-score, demonstrating the effectiveness of the proposed solution.
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Including Packages
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Base Paper
Complete Source Code
Complete Documentation
Complete Presentation Slides
Flow Diagram
Database File
Screenshots
Execution Procedure
Online Execution Support
Addons
Video Tutorials
Supporting Softwares
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00:00 Introduction
02:43 Reference paper
05:25 PPT Explanation
09:18 Proposed Solution
10:19 Overall Architecture
14:12 Project Demo
22:06 Conclusion