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International Journal for Research Trends and Innovation
International Peer Reviewed & Refereed Journals, Open Access Journal
ISSN Approved Journal No: 2456-3315 | Impact factor: 8.14 | ESTD Year: 2016
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Volume 10 | Issue 11
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Impact Factor : 8.14
Issue per Year : 12
Volume Published : 10
Issue Published : 114
Article Submitted : 18456
Article Published : 7827
Total Authors : 20673
Total Reviewer : 756
Total Countries : 142
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| Paper Title: | Brain stroke prediction from neuro images using deep learning |
| Authors Name: | Prathika , Jayashri , Premalatha , Shivaranjani , Deepika |
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IJRTI_203689
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| Published Paper Id: | IJRTI2505218 |
| Published In: | Volume 10 Issue 5, May-2025 |
| DOI: | |
| Abstract: | Brain stroke, a leading cause of disability and mortality worldwide, necessitates early detection and intervention for improved patient outcomes. This study proposes a novel approach for predicting brain stroke using magnetic resonance imaging (MRI) scan images and deep learning algorithm. A dataset comprising MRI scan images of patients with and without strokes is collected and pre-processed to enhance image quality. Features are extracted from the images, capturing radiomic information indicative of stroke pathology and implement deep learning model including convolutional neural networks (CNN), are trained on the extracted features to classify MRI scan images into types of strokes (ischemic and hemorrhagic) and non-stroke categories. Model performance is evaluated using standard metrics, and validated models are integrated into clinical workflows for real-time stroke prediction. The proposed approach offers a promising avenue for early detection and intervention in brain stroke cases, potentially improving patient outcomes and reducing the burden of stroke-related disabilities. The utilization of MRI scan images provides a non-invasive and highly detailed imaging modality for assessing brain health and detecting stroke-related abnormalities. This includes extracting radiomic features from MRI images, which capture subtle variations in tissue characteristics associated with stroke pathology. |
| Keywords: | Brain Stroke, Deep Learning, Convolutional Neural Networks (CNN), MRI Scan Images, Ischemic Stroke, Hemorrhagic Stroke, Radiomics, Medical Imaging, Stroke Prediction, Artificial Intelligence In Healthcare |
| Cite Article: | "Brain stroke prediction from neuro images using deep learning", International Journal of Science & Engineering Development Research (www.ijrti.org), ISSN:2455-2631, Vol.10, Issue 5, page no.c189-c197, May-2025, Available :http://www.ijrti.org/papers/IJRTI2505218.pdf |
| Downloads: | 000260 |
| ISSN: |
2456-3315 | IMPACT FACTOR: 8.14 Calculated By Google Scholar| ESTD YEAR: 2016 An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.14 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator |
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Published Paper ID: IJRTI2505218
Registration ID:203689
Published In: Volume 10 Issue 5, May-2025
DOI (Digital Object Identifier):
Page No: c189-c197 Country: Salem, Tamil Nadu, India Research Area: Engineering Publisher : IJ Publication Published Paper URL : https://www.ijrti.org/viewpaperforall?paper=IJRTI2505218 Published Paper PDF: https://www.ijrti.org/papers/IJRTI2505218 |
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ISSN: 2456-3315
Impact Factor: 8.14 and ISSN APPROVED,
Journal Starting Year (ESTD) : 2016
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