4 citations · 4 across the 5 of their papers we have counts for
5 papers
DDIAgents: Mechanism-Conditioned Context Flow for Drug-Drug Interaction Prediction
Zhenqian Shen, Yu Liu, Xiaoyi Fu +1
Drug-drug interaction (DDI) prediction is essential for medication safety, yet it requires reasoning over heterogeneous biomedical evidence whose relevance changes across interacti…
Case-Based Reasoning Enhances the Predictive Power of LLMs in Drug-Drug Interaction
Guangyi Liu, Yongqi Zhang, Xunyuan Liu +1
Drug-drug interaction (DDI) prediction is critical for treatment safety. While large language models (LLMs) show promise in pharmaceutical tasks, their effectiveness in DDI predict…
Benchmarking drug-drug interaction prediction methods: a perspective of distribution changes
Zhenqian Shen, Mingyang Zhou, Yongqi Zhang +1
Motivation: Emerging drug-drug interaction (DDI) prediction is crucial for new drugs but is hindered by distribution changes between known and new drugs in real-world scenarios. Cu…
Emerging Drug Interaction Prediction Enabled by Flow-based Graph Neural Network with Biomedical Network
Yongqi Zhang, Quanming Yao, Ling Yue +4
Accurately predicting drug-drug interactions (DDI) for emerging drugs, which offer possibilities for treating and alleviating diseases, with computational methods can improve patie…
Ensemble Learning for Graph Neural Networks
Zhen Hao Wong, Ling Yue, Quanming Yao
Graph Neural Networks (GNNs) have shown success in various fields for learning from graph-structured data. This paper investigates the application of ensemble learning techniques t…