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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: | Heart Disease Prediction: Unveiling Insights with K-Nearest Neighbours Algorithm |
| Authors Name: | C.Sameera Anjum , B.Umme Salma , C.Baby , K.Navitha , P.Shahinaz |
| Download E-Certificate: | Download |
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IJNRD_216905
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| Published Paper Id: | IJNRD2403650 |
| Published In: | Volume 9 Issue 3, March-2024 |
| DOI: | |
| Abstract: | Heart disease remains a significant health challenge in India, with millions affected annually, highlighting the pressing need for accurate diagnosis and effective management strategies. This chronic condition, characterized by inadequate blood supply to the body due to coronary artery narrowing or blockage, presents diverse symptoms including fatigue, swelling, and shortness of breath. Despite advancements in medical technology, diagnosing and treating heart disease remains complex, particularly in underserved regions. Cardiovascular diseases continue to be a leading cause of mortality in India, underscoring the urgency for improved healthcare delivery. In parallel, healthcare systems in countries like Indonesia face challenges due to a shortage of medical professionals, prompting research into innovative solutions for patient monitoring. Data mining techniques have emerged as valuable tools in healthcare diagnosis, offering insights into disease prediction and management. Various algorithms, including CART, ID3, Naive Bayes, and KNN, have been explored in predicting heart disease with varying degrees of accuracy. This study proposes a novel approach to heart disease prediction using the K-nearest neighbors (KNN) algorithm with instant measurement parameters. By leveraging body vital signs that can be instantly measured, this approach eliminates the need for invasive procedures, offering real-time monitoring particularly beneficial for home-based patient care. This innovative strategy aligns with advancements in patient monitoring technologies, aiming to enhance healthcare outcomes and reduce the burden of heart disease on the Indian healthcare system. |
| Keywords: | Machine Learning, KNN, Heart disease, Prediction, Health care |
| Cite Article: | "Heart Disease Prediction: Unveiling Insights with K-Nearest Neighbours Algorithm", International Journal of Novel Research and Development (www.ijnrd.org), ISSN:2456-4184, Vol.9, Issue 3, page no.g422-g426, March-2024, Available :http://www.ijnrd.org/papers/IJNRD2403650.pdf |
| Downloads: | 00039 |
| 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:IJNRD2403650 Registration ID: 216905 Published In: Volume 9 Issue 3, March-2024 DOI (Digital Object Identifier): Page No: g422-g426 Country: District, Andhra Pradesh, India Research Area: Computer Engineering Publisher : IJ Publication Published Paper URL : https://www.ijnrd.org/viewpaperforall?paper=IJNRD2403650 Published Paper PDF: https://www.ijnrd.org/papers/IJNRD2403650 |
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ISSN: 2456-4184
Impact Factor: 8.76 and ISSN APPROVED
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