Detecting drug–drug interactions (DDIs) is an essential step in drug development and drug
administration. Given the shortcomings of current experimental methods, the machine …

Graph neural network (GNN) is a formidable deep learning framework that enables the
analysis and modeling of intricate relationships present in data structured as graphs. In …

Drug repurposing has gained the attention of many in the recent years. The practice of
repurposing existing drugs for new therapeutic uses helps to simplify the drug discovery …

Unexpected drug–drug interactions (DDIs) are important issues for both pharmaceutical
research and clinical applications due to the high risk of causing severe adverse drug …

Urban tunnel infrastructure, crucial for societal well-being, depends on reliable Tunnel
Electromechanical Equipment (TEE), including ventilation, drainage, and lighting systems. A …

Background Drug-drug interaction events influence the effectiveness of drug combinations
and can lead to unexpected side effects or exacerbate underlying diseases, jeopardizing …

Numerous investigations increasingly indicate the significance of microRNA (miRNA) in
human diseases. Hence, unearthing associations between miRNA and diseases can …

Accurate prediction of drug-target binding affinity (DTA) is essential in the field of drug
discovery. Recently, scientists have been attempting to utilize artificial intelligence prediction …

Effective drug delivery is the cornerstone of modern healthcare, ensuring therapeutic
compounds reach their intended targets efficiently. This paper explores the potential of …

Food recommendation systems are becoming increasingly vital in modern society, given the
fast-paced lifestyle and diverse dietary habits. Existing research and implemented solutions …