Side Effect

Side effects, encompassing unintended consequences of treatments or interventions, are a major concern across various fields, from pharmacology and AI to engineering. Current research focuses on improving the prediction and mitigation of side effects using diverse approaches, including machine learning models like recurrent neural networks, graph neural networks, and matrix factorization methods, often leveraging multi-view data and knowledge graphs to enhance accuracy and interpretability. These advancements are crucial for improving drug safety, enhancing the reliability of AI systems, and optimizing the design of various technologies to minimize unintended negative consequences.