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INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT International Peer Reviewed & Refereed Journals, Open Access Journal ISSN Approved Journal No: 2456-4184 | Impact factor: 8.76 | ESTD Year: 2016 Scholarly open access journals, Peer-reviewed, and Refereed Journals, Impact factor 8.76 (Calculate by google scholar and Semantic Scholar | AI-Powered Research Tool) , Multidisciplinary, Monthly, Indexing in all major database & Metadata, Citation Generator, Digital Object Identifier(DOI) |
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| Paper Title: | MACHINE LEARNING ALGORITHM FOR STROKE DISEASE CLASSIFICATION AND ALERT SYSTEM |
| Authors Name: | Harshitha C , Neha.R , Mahanth.S , Charis.Susanna , Mr. Himansu Sekhar Rout |
| Download E-Certificate: | Download |
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IJNRD_212188
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| Published Paper Id: | IJNRDTH00103 |
| Published In: | Volume 9 Issue 1, January-2024 |
| DOI: | |
| Abstract: | Stroke is a leading cause of mortality and morbidity globally. Early detection and timely intervention can significantly reduce the risk of long-term disability and death. Machine learning algorithms have shown great promise in stroke diagnosis and classification, allowing for faster and more accurate decision- making. This research paper proposes a stroke disease classification and alert system using machine learning algorithms. The proposed system consists of three stages: data preprocessing, feature extraction, and classification. The data preprocessing stage involves the cleaning and normalization of data to removeany noise and inconsistencies. The feature extraction stage utilizes the extracted features from the data to generate a reduced feature set for efficient classification. Finally, the classification stage employs machine learning algorithms such as support vector machines (SVMs), decision trees, and random forests for stroke classification. The proposed system is trained and tested using a publicly available dataset of strokepatients. Experimental results demonstrate that the proposed system achieves high accuracy, sensitivity, and specificity in stroke classification. Furthermore, the proposed system includes an alert system that provides timely notifications to healthcare professionals for immediate intervention. The proposed system can be used as an auxiliary tool to assist healthcare professionals in stroke diagnosis and classification, providing faster and more accurate decision-making. |
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| Cite Article: | "MACHINE LEARNING ALGORITHM FOR STROKE DISEASE CLASSIFICATION AND ALERT SYSTEM", International Journal of Novel Research and Development (www.ijnrd.org), ISSN:2456-4184, Vol.9, Issue 1, page no.491-541, January-2024, Available :http://www.ijnrd.org/papers/IJNRDTH00103.pdf |
| Downloads: | 000118769 |
| ISSN: |
2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar| ESTD YEAR: 2016 An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.76 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:IJNRDTH00103 Registration ID: 212188 Published In: Volume 9 Issue 1, January-2024 DOI (Digital Object Identifier): Page No: 491-541 Country: bangalore40, karnataka, India Research Area: Computer Engineering Publisher : IJ Publication Published Paper URL : https://www.ijnrd.org/viewpaperforall?paper=IJNRDTH00103 Published Paper PDF: https://www.ijnrd.org/papers/IJNRDTH00103 |
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ISSN: 2456-4184
Impact Factor: 8.76 and ISSN APPROVED
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