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International Journal for Research Trends and Innovation
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ISSN Approved Journal No: 2456-3315 | Impact factor: 8.14 | ESTD Year: 2016
Scholarly open access journals, Peer-reviewed, and Refereed Journals, Impact factor 8.14 (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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Impact Factor : 8.14

Issue per Year : 12

Volume Published : 7

Issue Published : 74

Article Submitted : 3609

Article Published : 2079

Total Authors : 5515

Total Reviewer : 528

Total Countries : 39

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Paper Title: CHRONIC KIDNEY DISEASE METHODOLOGY BY USING MACHINE LEARNING
Authors Name: B.Sasi Varna , G.pravallika , Dr.A.Althaf Ali
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IJRTI_182299
Published Paper Id: IJRTi2206037
Published In: Volume 7 Issue 6, June-2022
DOI:
Abstract: Chronic kidney disease (CKD) is a global health issue that causes a high incidence of morbidity and death, as well as the onset of additional illnesses. Because there are no clear symptoms in the early stages of CKD, people frequently miss it. Early identification of CKD allows patients to obtain prompt therapy to slow the disease's development. Due of their rapid and precise identification capabilities, machine learning models can successfully assist doctors in achieving this aim. We present a machine learning framework for diagnosing CKD in this paper. The CKD data set was collected from the machine learning repository at the University of California, Irvine (UCI). As a result, it will determine whether or not a patient has CKD and, if so, whether or not further drugs should be taken. Six machine learning algorithms (Logistic Regression, AdaBoost, Random Forest, Decision Tree, and Gradient Boosting) were used to establish models.
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Cite Article: "CHRONIC KIDNEY DISEASE METHODOLOGY BY USING MACHINE LEARNING", International Journal of Science & Engineering Development Research (www.ijrti.org), ISSN:2455-2631, Vol.7, Issue 6, page no.207 - 216, June-2022, Available :http://www.ijrti.org/papers/IJRTi2206037.pdf
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ISSN: 2456-3315 | IMPACT FACTOR: 8.14 Calculated By Google Scholar| ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.14 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator
Publication Details: Published Paper ID: IJRTi2206037
Registration ID:182299
Published In: Volume 7 Issue 6, June-2022
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Page No: 207 - 216
Country: annamayya district, Andhra pradesh, India
Research Area: Master of Computer Application 
Publisher : IJ Publication
Published Paper URL : https://www.ijrti.org/viewpaperforall?paper=IJRTi2206037
Published Paper PDF: https://www.ijrti.org/papers/IJRTi2206037
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ISSN: 2456-3315
Impact Factor: 8.14 and ISSN APPROVED
Journal Starting Year (ESTD) : 2016

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