Chronic Kidney Disease Prediction Using Data Mining
J. Snegha, V. Tharani, S Preetha, R. Charanya, S. Durga Bhavani
20202020 International Conference on Emerging Trends in Information Technology and Engineering (ic-ETITE)27 citationsDOI
Abstract
In this doing of chronic kidney disease diagnosis, we have diagnosed kidney-related diseases using various data mining techniques, and in that, our overall objective is not to find the ideal solution but to indulge the solid diagnosis. In this proposal, we have used two data mining algorithms named Random Forest algorithm and Back Propagation Neural Network to diagnose the chronic kidney diseases and analyze it to lend the best algorithm for anticipating the chronic kidney diseases.
Topics & Concepts
Kidney diseaseComputer scienceData miningArtificial neural networkRandom forestDiseaseIdeal (ethics)KidneyArtificial intelligenceMachine learningMedicineIntensive care medicinePathologyInternal medicinePhilosophyEpistemologyArtificial Intelligence in HealthcareData Mining Algorithms and ApplicationsImbalanced Data Classification Techniques