This project implements a drug-disease association prediction model using Graph Convolutional Networks (GCN) with advanced data augmentation techniques. The model predicts novel drug-disease ...

I make short, to-the-point online math tutorials. I struggled with math growing up and have been able to use those experiences to help students improve in math through practical applications and tips.

Word Embedding (Python) is a technique to convert words into a vector representation. Computers cannot directly understand words/text as they only deal with numbers. So we need to convert words into ...

Abstract: Graph embeddings map graph-structured data into vector spaces for machine learning tasks. In Graph Neural Networks (GNNs), these embeddings are computed through message passing and support ...

Abstract: Predicting biomedical interactions is crucial for understanding various biological processes and drug discovery. Graph neural networks (GNNs) are promising in identifying novel interactions ...

ABSTRACT: Drug repositioning aims to identify new therapeutic applications for existing drugs offering a faster and more cost-effective alternative to traditional drug discovery. Since approved drugs ...