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International Journal for Research Trends and Innovation
International Peer Reviewed & Refereed Journals, Open Access Journal
ISSN Approved Journal No: 2456-3315 | Impact factor: 8.14 | ESTD Year: 2016
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Impact Factor : 8.14
Issue per Year : 12
Volume Published : 11
Issue Published : 117
Article Submitted : 21311
Article Published : 8476
Total Authors : 22301
Total Reviewer : 802
Total Countries : 156
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| Paper Title: | Early Detection of Chronic Kidney Disease using Machine Learning |
| Authors Name: | Lakshmi S , Dhanush A , Ilamathi M , Ramanan R S , Karthiban M J |
| Download E-Certificate: | Download |
| Author Reg. ID: |
IJRTI_186636
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| Published Paper Id: | IJRTI2305072 |
| Published In: | Volume 8 Issue 5, May-2023 |
| DOI: | |
| Abstract: | Abstract - Chronic kidney disease is the worldwide affected disease, people are unaware of the disease and know the seriousness in 3rd stage, nowadays people with various other medical report which are taken for different purposes can contain the valid information regarding the kidney disease with that information they can give the inputs like age, blood urea, blood glucose random, presence of pus cell, anemia, pedal edema, coronary artery disease, appetite, diabetes mellitus, blood pressure, hypertension, white blood cell count, red blood cell count, specific gravity, sodium, potassium, pus cell clumps, bacteria. We used machine learning technique and build a model with datasets and trained the model using random forest classifier algorithm where the predictions will be given with more accuracy. In our website we added information about the disease to get knowledge about chronic kidney disease (CKD), and we included BMI Calculator through which the user gives their height and weight and calculate the body mass index and know their normal health condition. The symptoms are the main parameters collected from user through website and result will generated for them. By this user can identify whether they are affected by the disease or not. |
| Keywords: | Machine Learning, Random Forest Classifier, Prediction, Symptoms, Body Mass Index |
| Cite Article: | "Early Detection of Chronic Kidney Disease using Machine Learning", International Journal for Research Trends and Innovation (www.ijrti.org), ISSN:2455-2631, Vol.8, Issue 5, page no.464 - 470, May-2023, Available :http://www.ijrti.org/papers/IJRTI2305072.pdf |
| Downloads: | 000205230 |
| 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 |
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Published Paper ID: IJRTI2305072
Registration ID:186636
Published In: Volume 8 Issue 5, May-2023
DOI (Digital Object Identifier):
Page No: 464 - 470 Country: Dharmapuri, Tamilnadu, India Research Area: Engineering Publisher : IJ Publication Published Paper URL : https://www.ijrti.org/viewpaperforall?paper=IJRTI2305072 Published Paper PDF: https://www.ijrti.org/papers/IJRTI2305072 |
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ISSN: 2456-3315
Impact Factor: 8.14 and ISSN APPROVED,
Journal Starting Year (ESTD) : 2016
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