MACHINE LEARNING ALGORITHM FOR STROKE DISEASE CLASSIFICATION AND ALERT SYSTEM

Registration ID: IJNRD_212188

Published ID: IJNRDTH00103

DOI: Click Here to Get

Harshitha C , Neha.R , Mahanth.S , Charis.Susanna , Mr. Himansu Sekhar Rout

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.

Published Paper   E-Certificate

Harshitha C, Neha.R, Mahanth.S, Charis.Susanna, & Mr. Himansu Sekhar Rout (January-2024). MACHINE LEARNING ALGORITHM FOR STROKE DISEASE CLASSIFICATION AND ALERT SYSTEM. INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT, 9(1), 491-541. https://ijnrd.org/papers/IJNRDTH00103.pdf

Volume 9 Issue 1, January-2024

Pages : 491-541

Paper Reg. ID: IJNRD_212188

Published Paper Id: IJNRDTH00103

Downloads: 000121987

Research Area: Computer Engineering 

Country: bangalore40, karnataka, India

Published Paper PDF: https://ijnrd.org/papers/IJNRDTH00103.pdf

Published Paper URL: https://ijnrd.org/viewpaperforall?paper=IJNRDTH00103

Journal Name: INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT(IJNRD)

ISSN: 2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar | ESTD YEAR: 2016

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