Drug Adverse Event Detection is a text dataset that simulates real-world scenarios involving multiple drug prescriptions for patients. It aims to study the risk of adverse drug reactions caused by the combined use of multiple drugs and has wide applications in adverse drug reaction detection, medical information extraction, clinical text analysis, and medical AI model training.

Data composition

Each patient record contains:

• Information on multiple prescription drugs
• Demographic characteristics and clinical background
• Target label for whether or not an adverse event occurs