Paper Title
PREDICTING STROKES USING A HYBRID STROKE PREDICTION TECHNIQUE BASED ON ENSEMBLE LEARNING (HSPEL)
Article Identifiers
Authors
Deepan L
Keywords
Strokes, Prediction, Hybrid,Predicting
Abstract
The negative impact of stroke in society has led to concerted efforts to improve the management and diagnosis of stroke. With an increased synergy between technology and medical diagnosis, caregivers create opportunities for better patient management by systematically mining and archiving the patients’ medical records. Therefore, it is vital to study the interdependency of these risk factors in patients’ health records and understand their relative contribution to stroke prediction. This paper systematically analyzes the various factors in electronic health records for effective stroke prediction. Using various statistical techniques and ensemble learning, the most important factors for stroke prediction are assessed and the patients’ dataset samples classified. The proposed scheme called HSPELs (Heart Stroke Prediction with Ensemble Learning) predicts the risks of patients being affected with heart strokes. The schema achieved an accuracy of approximately 93 percent in classifying samples that are like to be affected by stroke..
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"PREDICTING STROKES USING A HYBRID STROKE PREDICTION TECHNIQUE BASED ON ENSEMBLE LEARNING (HSPEL)", IJNRD - INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT (www.IJNRD.org), ISSN:2456-4184, Vol.8, Issue 9, page no.c453-c459, September-2023, Available :https://ijnrd.org/papers/IJNRD2309251.pdf
Issue
Volume 8 Issue 9, September-2023
Pages : c453-c459
Other Publication Details
Paper Reg. ID: IJNRD_205522
Published Paper Id: IJNRD2309251
Downloads: 000121177
Research Area: Electrical EngineeringÂ
Country: Thiruvallur District, Tamil Nadu, India
Published Paper PDF: https://ijnrd.org/papers/IJNRD2309251.pdf
Published Paper URL: https://ijnrd.org/viewpaperforall?paper=IJNRD2309251
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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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This work is licensed under a Creative Commons Attribution 4.0 International License and The Open Definition


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