AntLion Optimization Algorithm based Type II Diabetes Mellitus Prediction

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dc.contributor.authorAnbalagan, A.
dc.contributor.authorBaskar, C.
dc.contributor.authorDeekshetha, H.R.
dc.contributor.authorReshma, S.
dc.contributor.authorVijayalakshmi, M.
dc.contributor.authorArumuga Perumal, D.
dc.date.accessioned2026-02-06T06:35:26Z
dc.date.issued2022
dc.description.abstractDiabetes Mellitus is one of the common diseases prevailing in most developed and developing countries. In recent decades, there has been a huge rise in diabetes patients in India. Based on recent statistics, nearly 72.96 million young people are suffering from diabetes. Thus, it is essential to diagnose diabetes at an early stage. In this work, the PIMA dataset is used to design an optimized and super-vised learning model based on K-nearest neighbor classification. The optimization algorithm used to generate useful features to predict diabetes mellitus is the Antlion optimization algorithm. The proposed work yields an accuracy of 80% for the selected features like Pregnancy, BMI, BP, Age, Glucose, and Diabetes Pedigree Function. © 2022 IEEE.
dc.identifier.citationProceedings of 2022 International Conference on Intelligent Innovations in Engineering and Technology, ICIIET 2022, 2022, Vol., , p. 280-285
dc.identifier.urihttps://doi.org/10.1109/ICIIET55458.2022.9967563
dc.identifier.urihttps://idr.nitk.ac.in/handle/123456789/29839
dc.publisherInstitute of Electrical and Electronics Engineers Inc.
dc.subjectAntLion algorithm
dc.subjectDiabetes
dc.subjectKNN classification
dc.subjectPIMA Dataset
dc.titleAntLion Optimization Algorithm based Type II Diabetes Mellitus Prediction

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