EEG Data for Patients Receiving Intravenous Antibiotic Medication

In this dataset, we conduct a biological data collectionand analysis study for patients undergoing routine plannedtreatment. The acquired data (i.e., Electroencephalogram (EEG)and routine observational data such as temperature and bloodpressure) are processed using different machine learning anddeep learning models to learn the dynamic properties of brainelectrical activity from different patients. Thus, the primaryobjective of our study is the safe collection of EEG data frompatients receiving antibiotic therapy, in addition to analyzingthe acquired data for detecting the medication side effects, i.e.,that might indicate risk of seizure. Indeed, we propose twomachine learning models to analyze the acquired data fromdiverse patients: before, during, and after taking the medications.