Personalized Drug-Disease prediction using Multiple Linear Regression with ReLU
S. Vijaya · Journal of Physics Conference Series · 2021
Abstract Predicting models for personalized Drugs related to specific disease are essential, as traditional methods are expensive and time consuming. The most challenging task in personalized medicine is predicting the status of disease from high dimensionality data. In the biomedical domain the association between drugs and disease plays a vital role as the same drug may treat similar diseases. For the good adaptability to complex and nonlinear behaviour data, Multiple Linear Regression method with ReLU Activation function is used for calculation and to fit the model with Drug –Disease dataset. Based on the results the drug or combination of drugs that treat a specific disease is predicted efficiently.