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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: | Multiple Disease Prediction System Using Machine Learning |
| Authors Name: | Emani Bhargavi , Dr. R. Srinivasa Rao , D. Purnachandra Rao , B. Kanthi Kumar , D. Venkatesh |
| Download E-Certificate: | Download |
| Author Reg. ID: |
IJNRD_190526
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| Published Paper Id: | IJNRD2304131 |
| Published In: | Volume 8 Issue 4, April-2023 |
| DOI: | |
| Abstract: | People are becoming increasingly susceptible to high-risk illnesses like chronic diabetes, heart disease, Parkinson’s disease etc. The mortality ratio is prevalent nowadays due to the enormous number of deaths. Many of the current machine learning models for health care analysis focus on a single disease at a time. One analysis is for diabetes, one for the heart, and one for Parkinson's of that nature. There is no standard system that allows one analyst to forecast more than one disease at a time. They also provide a result with low accuracy and precision. Then that lower accuracy puts the patient's life in danger. Hence, using machine learning we are suggesting a predictive system, the so-called Multiple Disease Prediction System which is used to predict diseases accurately and simultaneously forecast several diseases in one shot. Diabetes, heart disease, and Parkinson's disease are the three diseases we have currently taken into consideration. Future, many more diseases may be added. Here, we employ machine learning (ML) techniques like SVM for (diabetes and Parkinson's) and Logistic Regression for Heart Disease for diseases prediction. The user must enter many disease-related parameters before the system displays a result indicating whether the user has the disease or not. It aids in the processing of the massive volumes of data produced by the medical sector and significantly shortens the time it takes for doctors to detect a patient's disease at an early stage. It also encourages the adoption of preventative measures to lengthen the patient's life expectancy. |
| Keywords: | Machine Learning, Artificial Intelligence, SVM, Logistic Regression, Diabetes, Heart, Parkinson’s. |
| Cite Article: | "Multiple Disease Prediction System Using Machine Learning", International Journal of Novel Research and Development (www.ijnrd.org), ISSN:2456-4184, Vol.8, Issue 4, page no.b270-b282, April-2023, Available :http://www.ijnrd.org/papers/IJNRD2304131.pdf |
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| 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:IJNRD2304131 Registration ID: 190526 Published In: Volume 8 Issue 4, April-2023 DOI (Digital Object Identifier): Page No: b270-b282 Country: Krishna District, Andhra Pradesh, India Research Area: Other Publisher : IJ Publication Published Paper URL : https://www.ijnrd.org/viewpaperforall?paper=IJNRD2304131 Published Paper PDF: https://www.ijnrd.org/papers/IJNRD2304131 |
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ISSN: 2456-4184
Impact Factor: 8.76 and ISSN APPROVED
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