AkramOM606/DeepLearning-CNN-Brain-Stroke-Prediction
This repository contains a Deep Learning model using Convolutional Neural Networks (CNN) for predicting strokes from CT scans. The model aims to assist in early detection and intervention of strokes, potentially saving lives and improving patient outcomes.
Trained on Kaggle CT scan datasets with binary classification (stroke vs. normal cases), the model leverages CNN architecture to extract spatial features like edges and patterns critical for detecting ischemic indicators in brain imaging. Built with standard deep learning frameworks, it provides an end-to-end pipeline from image preprocessing through classification, suitable for integration into medical imaging workflows requiring automated screening capabilities.
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Feb 22, 2025
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