Multimodal Cnn-ddi: Using Multimodal Cnn For Drug To Drug Interaction Associated Events

This article discusses the importance of discovering drug-drug interactions (DDIs) in order to improve the drug discovery and patient recovery process for deadly diseases. It also explores the use of machine learning and deep learning techniques to predict DDIs, specifically through the use of a Multi-Modal Convolutional Neural Network. The proposed method, MMCNN-DDI, utilizes multiple features of drugs and calculates similarities using Jaccard similarity measures to predict drug-drug interaction events.