What question did this study set out to answer?

To utilize machine learning and deep learning techniques for accurate brain stroke detection from medical images.

April 24, 2026Open Access

Brain Stroke Detection Using Machine Learning And Deep Learning

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Machine Learning and Deep Learning methods detect strokes in medical images, indicating effective early diagnosis tools.

To utilize machine learning and deep learning techniques for accurate brain stroke detection from medical images.
Implemented GUI for dataset handling and image classification.
Used Convolutional Neural Networks (CNN) for stroke image classification and Support Vector Machines (SVM) for comparison.
Conducted preprocessing, feature extraction, and model training with frameworks like PyTorch and TensorFlow.
CNN achieved 98% accuracy in classifying stroke images, outperforming SVM's 59%.
The model successfully differentiated between normal and stroke-affected brain images during testing.
Incorporating clinical data improved stroke prediction accuracy.

Prakash et al. (2026) studied this question.

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