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Leukemia Drug Prediction Using Machine Learning Techniques with Feature Engineering


Dr.N. Priya and G. Shobana
Abstract

Researchers have been working towards various strategies to produce effective anticancer drugs. Leukemia is a type of cancer disease that affects people of all ages throughout the globe and is caused by the abnormal cells produced by the bone marrow. Numerous clinical trials are conducted by the biomedical researchers to understand the biological activities, pharmaceutical properties and toxicity prediction of the newly synthesized drug, which involves huge cost and time. In this paper, various machine learning models like Support Vector Machine, Decision Tree, Artificial Neural Network, Random Forest were employed to predict the Leukemia drug among several other drugs. Furthermore, the features are engineered using Principal Component Analysis and Recursive Feature Elimination to achieve higher prediction accuracy. Artificial Neural Network machine learning model had better prediction accuracy.

Volume 12 | 04-Special Issue

Pages: 141-146

DOI: 10.5373/JARDCS/V12SP4/20201475