• Preventive medicine · Sep 2023

    Predicting diabetes with multivariate analysis an innovative KNN-based classifier approach.

    • B V V Siva Prasad, Sapna Gupta, Naiwrita Borah, R Dineshkumar, Hitendra Kumar Lautre, and B Mouleswararao.
    • Department of CSE (School of Engineering), Anurag University, Hyderabad, Telangana, India. Electronic address: drbvvsivaprasad@gmail.com.
    • Prev Med. 2023 Sep 1; 174: 107619107619.

    AbstractDiabetes seems to be a severe protracted disease or combination of biochemical disorders. A person's blood glucose (BG) levels remain elevated for an extended period because tissues lack and non-reaction to hormones. Such conditions are also causing longer-term obstacles or serious health issues. The medical field handles a large amount of very delicate data that must be handled properly. K-Nearest Neighbourhood (KNN) seems to be a common and straightforward ML method for creating illness threat prognosis models based on pertinent clinical information. We provide an adaptable neuro-fuzzy inference K-Nearest Neighbourhood (AF-KNN) learning-dependent forecasting system relying on patients' behavioural traits in several aspects to obtain our aim. That method identifies the best proportion of neighborhoods having a reduced inaccuracy risk to improve the predicting performance of the final system.Copyright © 2023 Elsevier Inc. All rights reserved.

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