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Volume 11, Issue 5 (May 2025)

Neural Network-powered Brain Tumor Detection Using Machine Learning

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7.883
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Volume 12 Issue 07

July 2026

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Author(s)

Mohammed Gufran Mohammed Zubairulla Khan Mohin R Pinjar Sona J M

Abstract

Detecting Brain Tumors Early Is Vital For Giving Patients The Best Chance At Successful Treatment And Recovery. This Project Introduces A User-friendly Web Application Designed To Help With The Early Detection Of Brain Tumors Using MRI Scans And Artificial Intelligence (AI). The System Allows Both Doctors And Patients To Upload Brain MRI Images Taken From Four Common Angles: Top, Bottom, Left, And Right. Once Uploaded, These Images Are Processed By A Secure Backend System Built With The Flask Framework. A Pre-trained Deep Learning Model—specifically, A Convolutional Neural Network (CNN)—analyses The Scans To Look For Signs Of Brain Tumors. After The Analysis, The Application Creates A Simple, Easy-to-understand Report That Includes Patient Details, The AI’s Prediction, And A Confidence Score (set Above 90% For Demonstration). The Platform Is Designed To Be Intuitive, Requiring No Technical Background To Use. While It’s Not Meant To Replace Professional Medical Diagnosis, It Can Serve As A Helpful Early Screening Tool, Particularly In Areas With Limited Access To Healthcare. This Work Demonstrates How AI-powered Tools Can Support Faster, More Accessible Medical Insights And Improve Diagnostic Processes.


Keywords

Brain Tumor Detection MRI Analysis Deep Learning AI Flask Medical Imaging Diagnostic Support.

Paper ID

IJSARTV11I5103673

Publication Date

May 25, 2025

Research Area

Information Science And Engineering

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