What question did this study set out to answer?

The aim is to enhance ischemic stroke detection using advanced machine learning and deep learning models.

April 15, 2026International Journal of Scientific Development and ResearchOpen Access

An Improved Concatenation of Deep Learning Models for Predicting and Interpreting Ischemic Stroke

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Analysis reveals deep learning techniques effectively classify ischemic strokes in medical images, suggesting improved detection.

The aim is to enhance ischemic stroke detection using advanced machine learning and deep learning models.
Utilized a dataset with categorized images of ischemic and normal cases
Performed feature extraction and data preprocessing
Split data into training and testing sets
Applied Support Vector Machine and Convolutional Neural Network for classification
SVM achieved 85% accuracy in stroke image classification
CNN achieved a significantly higher accuracy of 98%
CNN was effective in distinguishing between ischemic and normal cases in new test images

Thrisha et al. (2026) studied this question.

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