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- W4384025344 abstract "Diabetes 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." @default.
- W4384025344 created "2023-07-13" @default.
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- W4384025344 date "2023-09-01" @default.
- W4384025344 modified "2023-09-26" @default.
- W4384025344 title "Predicting diabetes with multivariate analysis an innovative KNN-based classifier approach" @default.
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- W4384025344 doi "https://doi.org/10.1016/j.ypmed.2023.107619" @default.
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