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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: | Effective Heart Disease Prediction Using Hybrid Machine Learning Techniques |
| Authors Name: | Tanaya Chaporkar , Mayuresh Khanzode , Hemant Malpani , Tushar Joshi , Prof. H. D. Misalkar |
| Download E-Certificate: | Download |
| Author Reg. ID: |
IJNRD_218985
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| Published Paper Id: | IJNRD2404581 |
| Published In: | Volume 9 Issue 4, April-2024 |
| DOI: | |
| Abstract: | — The diagnosis of heart disease is the most difficult task in the medical field. The diagnosis of heart disease is difficult as a decision relied on grouping of large clinical and pathological data. Due to this complication, the interest increased in a significant amount between the researchers and clinical professionals about the efficient and accurate heart disease prediction. In case of heart disease, the correct diagnosis in early stage is important as time is the very important factor. Heart disease is the principal source of deaths widespread, and the prediction of heart disease is significant at an untimely phase. Machine learning in recent years has been the evolving, reliable and supporting tools in medical domain and has provided the greatest support for predicting disease with correct case of training and testing. The main idea behind this work is to study diverse prediction models for the heart disease and selecting important heart disease feature using hybrid machine learning algorithm. Logistic regression and gradient boosting are Machine Learning algorithm which has the high accuracy compared to other Supervised Machine Learning algorithms. By using logistic regression and gradient boosting algorithm, we are going to predict if a person has heart disease or not. |
| Keywords: | Machine Learning, Logistic Regression, Gradient Boosting Algorithm, Hybrid machine learning algorithms. |
| Cite Article: | "Effective Heart Disease Prediction Using Hybrid Machine Learning Techniques", International Journal of Novel Research and Development (www.ijnrd.org), ISSN:2456-4184, Vol.9, Issue 4, page no.f667-f678, April-2024, Available :http://www.ijnrd.org/papers/IJNRD2404581.pdf |
| Downloads: | 00020 |
| 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:IJNRD2404581 Registration ID: 218985 Published In: Volume 9 Issue 4, April-2024 DOI (Digital Object Identifier): Page No: f667-f678 Country: Amravati, Maharashtra, India Research Area: Information Technology Publisher : IJ Publication Published Paper URL : https://www.ijnrd.org/viewpaperforall?paper=IJNRD2404581 Published Paper PDF: https://www.ijnrd.org/papers/IJNRD2404581 |
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ISSN: 2456-4184
Impact Factor: 8.76 and ISSN APPROVED
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