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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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Impact Factor : 8.14
Issue per Year : 12
Volume Published : 10
Issue Published : 115
Article Submitted : 19688
Article Published : 8087
Total Authors : 21392
Total Reviewer : 770
Total Countries : 147
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| Paper Title: | Advancing Brain Stroke Classification: Leveraging Deep Learning on CT Scans for Enhanced Prediction Accuracy |
| Authors Name: | Ch.Ramesh , K.Madhuri , B.Geethika Sai , O.Harika , K.Laksnmi Revanth |
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IJRTI_189336
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| Published Paper Id: | IJRTI2404103 |
| Published In: | Volume 9 Issue 4, April-2024 |
| DOI: | |
| Abstract: | Brain stroke is one of the primary causes of adult humanity and disease. Since this is a medical emergency, you must get care as soon as you can. Getting medical attention as soon as possible will help avoid brain damage and other issues. Numerous prediction techniques, including those that help clinicians prescribe therapy for diseases they prescribe, have been widely employed in clinical decision-making. These techniques include anticipating the occurrence and outcome of diseases. This approach of predicting analytical techniques for stroke was implemented by employing a deep learning model on a brain disease dataset. Here, we predict and categorize strokes using a dataset of CT (computed tomography) images. For accurate prediction, the current system uses machine learning (ML) computations such as logistic regression, decision tree classification, random forest classification, KNN, and SVM, taking into account a variety of criteria. The constructed model looks into how a deep learning model might be used to categorize photos of brain strokes. The model uses MobileNetV2 and ResNet152 pre-trained architectures to increase classification accuracy. The model's ability to increase brain stroke classification accuracy is highlighted in this paper, which may contribute to early detection and better patient outcomes. |
| Keywords: | Deep Learning models, Image feature extraction. |
| Cite Article: | "Advancing Brain Stroke Classification: Leveraging Deep Learning on CT Scans for Enhanced Prediction Accuracy", International Journal of Science & Engineering Development Research (www.ijrti.org), ISSN:2455-2631, Vol.9, Issue 4, page no.748 - 752, April-2024, Available :http://www.ijrti.org/papers/IJRTI2404103.pdf |
| Downloads: | 000205174 |
| 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: IJRTI2404103
Registration ID:189336
Published In: Volume 9 Issue 4, April-2024
DOI (Digital Object Identifier):
Page No: 748 - 752 Country: Krishna, Andhra pradesh, India Research Area: Information Technology Publisher : IJ Publication Published Paper URL : https://www.ijrti.org/viewpaperforall?paper=IJRTI2404103 Published Paper PDF: https://www.ijrti.org/papers/IJRTI2404103 |
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ISSN: 2456-3315
Impact Factor: 8.14 and ISSN APPROVED,
Journal Starting Year (ESTD) : 2016
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