GEFA: Early Fusion Approach in Drug-Target Affinity Prediction

Abstract

Aiming to improve the accuracy of CNN-based doctor recommendation systems, this research contrasts XGBoost (XGB) with CNNs. College-Related Materials: In this research, the accuracy was evaluated using two deep learning models: XGBoost (XGB) and CNN. The sample size was N=10, and the power was 80%. A significance score of (p=0.144) (p<0.05) indicates that the statistical analysis did not find a significant difference between the two groups studied in this study. Compared to XGB's 88.19% accuracy rating, CNN's is far higher at 90.15 percent. Lastly, we compare the XGBoost method to a medical recommendation system that uses Convolutional Neural Networks (CNNs). When it comes to online doctor recommendations, CNN is obviously the superior algorithm when compared to XGBoost.