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Classifying clinically actionable genetic mutations using KNN and SVM
2021
Indonesian Journal of Electrical Engineering and Computer Science
Cancer is one of the major causes of death in humans. Early diagnosis of genetic mutations that cause cancer tumor growth leads to personalized medicine to the decease and can save the life of majority of patients. With this aim, Kaggle has conducted a competition to classify clinically actionable gene mutations based on clinical evidence and some other features related to gene mutations. The dataset contains 3321 training data points that can be classified into 9 classes. In this work, an
doi:10.11591/ijeecs.v24.i3.pp1672-1679
fatcat:uap5wbi3ybdujkbtwjjrdmoqti