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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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Issue: March 2026
Volume 11 | Issue 3
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Impact Factor : 8.14
Issue per Year : 12
Volume Published : 11
Issue Published : 118
Article Submitted : 21574
Article Published : 8528
Total Authors : 22430
Total Reviewer : 805
Total Countries : 159
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| Paper Title: | ACHYUTA 2.0 ( Advanced Cluster Health Sector Yonder Unification to App 2.0 Using Machine Learning) |
| Authors Name: | Amit Kumar Jha , Lalita panika , Siddhant Shukla , Raj Sahu , Aryan Prithwani |
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IJRTI_207786
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| Published Paper Id: | IJRTI2511114 |
| Published In: | Volume 10 Issue 11, November-2025 |
| DOI: | |
| Abstract: | The fast pace of innovation in healthcare technology means it is important to predict diseases early to avoid serious health issues and to intervene appropriately in the health system. In this paper, we introduce ACHYUTA 2.0, a web application based machine learning system to predict the risk of three prominent diseases, namely, Diabetes, Kidney Disease, and COVID-19. The application uses machine learning algorithms and publicly available datasets of general population health parameters inputted by the user. For Diabetes we uses svm, for Kidney Disease a Random Forest Classifier is utilized, while the XGBRegressor predicts COVID-19 new cases from epidemiological data. The application performs well in real time prediction, with an accuracy of 0.9225 in training data and 0.805 in testing data, along with this the f1-score for kidney disease prediction is 0.92 and in addition to that we have achieved R2 score of 0.9978 for covid disease prediction. The user interface is easy to use, and provides immediate assessment of health risks, and prevention. |
| Keywords: | Artifical Intelligence, Machine Learning, Healthcare Analytics, Predictive Modeling, Web-Based Health System, Flask Framework |
| Cite Article: | "ACHYUTA 2.0 ( Advanced Cluster Health Sector Yonder Unification to App 2.0 Using Machine Learning)", International Journal for Research Trends and Innovation (www.ijrti.org), ISSN:2455-2631, Vol.10, Issue 11, page no.b111-b114, November-2025, Available :http://www.ijrti.org/papers/IJRTI2511114.pdf |
| Downloads: | 000228 |
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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: IJRTI2511114
Registration ID:207786
Published In: Volume 10 Issue 11, November-2025
DOI (Digital Object Identifier):
Page No: b111-b114 Country: RAIPUR, Chhattisgarh, India Research Area: Computer Science & Technology Publisher : IJ Publication Published Paper URL : https://www.ijrti.org/viewpaperforall?paper=IJRTI2511114 Published Paper PDF: https://www.ijrti.org/papers/IJRTI2511114 |
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ISSN: 2456-3315
Impact Factor: 8.14 and ISSN APPROVED,
Journal Starting Year (ESTD) : 2016
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