NeuroGenius: A Machine Learning based Brain Tumour Detection Platform

Abstract

In today’s times, the increasing problem of brain tumor as Neurological disorder caters to the urgent need for an accurate, efficient, and scalable diagnosis that can be achieved at a high quality. Traditional diagnostics have been successful in the past, but they are too time-consuming to allow early detection and timely treatment. This paper presents NeuroGenius, an intelligent Healthcare system that uses machine learning algorithms onto medical imaging techniques, like MRI and CT scans that help us detect brain tumors. This paper presents NeuroGenius, a smart healthcare platform that has machine learning algorithms for MRI and CT scan technologies quickly detect brain tumors. The framework that we have used relies on preprocessing, feature extraction, and classification techniques by using Convolutional Neural Network (CNNs) based models and Support Vector Machines (SVMs) to achieve reliable results. It does not use any standalone heavy deep learning model but rather focuses on high scalability, and easy integration into real world. Clinical workflows and early detection when combined with easy data handling make NeuroGenius practical and secure. This is a very viable solution for both academic research and clinical use. Also, it supports health professionals through better diagnostic accuracy, reduced workload, and better patient results.