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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: | Early Detection of Heart Disease through Machine Learning Analysis of Audio Signals |
| Authors Name: | Divyanshu Singh , Abhay Pratap Singh , Aryan Singh , Isha Agrawal , Rahul Kumar |
| Download E-Certificate: | Download |
| Author Reg. ID: |
IJNRD_218802
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| Published Paper Id: | IJNRD2404473 |
| Published In: | Volume 9 Issue 4, April-2024 |
| DOI: | |
| Abstract: | Heart disease is the world's most pressing issue. Heart disease causes more deaths than any other cause during a first heart attack.However, not just for Heart attacks have been linked to issues with the ventricle, lung cancer, breast cancer, and other conditions. Having a framework that can instantly and effectively identify the prevalence of cardiac disease in thousands of samples is crucial. In this paper the potential of ten classification techniques was evaluated of prediction of heart disease. SVM.CNN, KNN.A variety of machine learning models specifically designed for heart disease prediction make up the suggested method. SVM, K-Nearest Neighbors (KNN), Convolutional Neural Networks (CNN) enhanced with Particle Swarm Optimization (PSO), KNN optimized with Genetic Algorithm (GA), KNN optimized with Bat Algorithm (BAT), and KNN optimized with Grey Wolf Optimization (GWO) are some of these models. Using medical profiles such as a Heart Beat Sound It can forecast a patient's likelihood of developing heart disease. In light of this, the medical community isinterested in identifying and preventing cardiac disease. The investigation has demonstrated that, incomparison to earlier approaches, classificationbased procedures yield more accuracy and contribute with greater effectiveness. |
| Keywords: | Heart disease, Disease diagnosis, Prediction, Classification techniques, Heartbeat Sound, PSO, GA, BAT, GWO |
| Cite Article: | "Early Detection of Heart Disease through Machine Learning Analysis of Audio Signals", International Journal of Novel Research and Development (www.ijnrd.org), ISSN:2456-4184, Vol.9, Issue 4, page no.e704-e709, April-2024, Available :http://www.ijnrd.org/papers/IJNRD2404473.pdf |
| Downloads: | 00021 |
| 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:IJNRD2404473 Registration ID: 218802 Published In: Volume 9 Issue 4, April-2024 DOI (Digital Object Identifier): Page No: e704-e709 Country: Mathura, uttar pradesh, India Research Area: Computer Science & Technology Publisher : IJ Publication Published Paper URL : https://www.ijnrd.org/viewpaperforall?paper=IJNRD2404473 Published Paper PDF: https://www.ijnrd.org/papers/IJNRD2404473 |
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ISSN: 2456-4184
Impact Factor: 8.76 and ISSN APPROVED
Journal Starting Year (ESTD) : 2016
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