A fuzzy logic based predictive model for early detection of stroke.

UbiComp '18: The 2018 ACM International Joint Conference on Pervasive and Ubiquitous Computing Singapore Singapore October, 2018(2018)

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摘要
In recent time stroke becomes life threatening deadly cause and it just increasing at global alarming state. Stroke occurs when blood flow interrupt in brain. Now it is highly demanded to use computational expertise for detecting stroke. The proposed system of stroke prediction focuses potential and crucial risk factors of stroke to design the model. The data set was collected from Dhaka medical college, situated in Bangladesh and by using data mining technique; the unnecessary risk factors are pruned. By using Fuzzy logic Inference System and C-means fuzzy classifier, input data is classified. Later on, we generate fuzzy if-then rule by using fuzzy Inference System to make a better prediction model. The developed predictive model gained satisfaction of physicians' as it provides higher accuracy. The developed model will not only aid needy one but also it will help medical experts.
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关键词
Fuzzy logic, Stroke, Bangladesh, FIS, C classifier, fuzzy inference, risk factor, data mining, ANFIS, clustering, prediction, detect, fuzzy model
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