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Original Article

AI-Based Brain Stroke Detection

  • Paper ID 937
  • Volume 6, Issue 2
  • Pages 170-173
  • Published Online: March-April 2025
  • 1 Views
Open Access Peer Reviewed Crossref DOI

Authors

  • Jayant Rohankar1
  • Sidhesh Bankar2

12IT, St. Vincent Pallotti College of Engineering & Technology/ RTMNU, Nagpur, Maharashtra, India.

Article Information

Published Online
March-April 2025
Pages
170-173
Article Type
Original Article
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Abstract

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Brain stroke is a critical neurological emergency, often causing long-term disability or mortality if not diagnosed in time. This research presents a practical implementation of an AI-based framework using Convolutional Neural Networks (CNNs) for detecting brain strokes from CT images and predicting severity levels. By leveraging deep learning and labeled neuroimaging datasets, our model demonstrates early and accurate classification of stroke versus non-stroke conditions, along with severity estimation. The model was trained on a curated dataset with structured preprocessing, and the pipeline includes performance metrics for reliability. We further address key considerations like model generalizability, data governance, and explain ability. The paper contributes both a replicable codebase and an empirical foundation for clinical AI deployment.

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  • ISSN 2582-8746
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