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)
Chronic Kidney Disease and Diabetes are major chronic illnesses requiring early detection to avoid complications. This project introduces a web-based prediction system using machine learning. For CKD, three feature selection methods Anova,Mutual Information,RFE with random forest were combined to identify impotent key clinical features, which improved model efficiency and accuracy. CatBoost 0.98, while for diabetes, XGboost model reached 0.82 accuracy. The final models were deployed in a user-friendly web platform.
"Comparative Prediction Analysis using ML Algorithms for CKD and Diabetes", International Journal for Research Trends and Innovation (www.ijrti.org), ISSN:2455-2631, Vol.10, Issue 11, page no.a133-a140, November-2025, Available :http://www.ijrti.org/papers/IJRTI2511019.pdf
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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