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Hybrid artificial fish particle swarm optimizer and kernel extreme learning machine for type-II diabetes predictive model
AbstractThe World Health Organization(WHO) estimated that in 2016, 1.6 million deaths caused were due to diabetes. Precise and on-time diagnosis of type-II diabetes is crucial to reduce the risk of various diseases such as heart disease, stroke, kidney disease, diabetic retinopathy, diabetic neuropathy, and macrovascular problems. The non-invasive methods like machine learning are reliable and efficient in classifying the people subjected to type-II diabetics risk and healthy people into two different categories. This present study aims to develop a stacking-based integrated kernel extreme learning machine (KELM) model for...
Source: Medical and Biological Engineering and Computing - March 18, 2021 Category: Biomedical Engineering Source Type: research
