Recently, using artificial intelligence (AI) in drug discovery has received much attention
since it significantly shortens the time and cost of developing new drugs. Deep learning (DL) …

Background Artificial intelligence (AI) and the Internet of Intelligent Things (IIoT) are
promising technologies to prevent the concerningly rapid spread of coronavirus disease …

The use of deep learning (DL) for the analysis and diagnosis of biomedical and health care
problems has received unprecedented attention in the last decade. The technique has …

Abstract Drug-Drug Interaction (DDI) prediction is one of the most critical issues in drug
development and health. Proposing appropriate computational methods for predicting …

The COVID-19 pandemic has wreaked havoc in every country in the world, with serious
health-related, economic, and social consequences. Since its outbreak in March 2020, many …

Abstract Recently Artificial Intelligence (AI) has not only been used to diagnose the disease
but also to cure the disease. Researchers started using AI for drug discovery. Predicting the …

Despite huge technological advances in the capabilities to capture, store, link and analyse
data electronically, there has been some but limited impact on routine pharmacovigilance …

Approved drugs for sale must be effective and safe, implying that the drug's advantages
outweigh its known harmful side effects. Side effects (SE) of drugs are one of the common …

In this study, we developed a hybrid deep learning (DL) model, which is one of the first
interpretable hybrid DL models with Inception modules, to give a descriptive prediction of …

Adverse drug reactions (ADR) are important information for verifying the view of the patient
on a particular drug. Regular user comments and reviews have been considered during the …