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- W4378189849 abstract "Based on data from the Indonesian Ministry of Health, there has been an increase in the number of stroke cases by 3.9% from 2013 to 2018. Nationally, the number of stroke cases often occurs in groups that have an age range between 55-64 years and the least occur in the 15-24 age range. A stroke (Cerebrovascular Accident) is a condition where blood flow to the brain is suddenly interrupted or reduced. This can be caused by a blockage or rupture of blood vessels so that cells in the brain area do not get a blood supply that is full of nutrients and oxygen. Early detection is needed which aims to reduce the number of potential deaths from stroke. Stroke prediction is still a challenge in the field of medicine, one of the reasons is the volume of data on medical data which has high heterogeneity and complexity. Machine learning techniques are data analysis models that can be used to predict stroke. Various machine learning models have been proposed by previous researchers, one of which is the Support Vector Machine. This study tries to re-implement the SVM algorithm to get better performance results than previous studies. In this study, the accuracy value was 100% and ROC-AUC values were 100%. Further studies need to be carried out regarding the results obtained to reach 100%." @default.
- W4378189849 created "2023-05-26" @default.
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- W4378189849 date "2023-04-20" @default.
- W4378189849 modified "2023-10-07" @default.
- W4378189849 title "STROKE PREDICTION USING A SUPPORT VECTOR MACHINE (SVM)" @default.
- W4378189849 doi "https://doi.org/10.59688/bufnets.v1i1.5" @default.
- W4378189849 hasPublicationYear "2023" @default.
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