Abstract: Continuous temperature monitors can be used to collect frequent temperature data over large periods of time. A machine learning system trained with collected temperature data can be used to predict future temperature data for patients. Such predictions can be clinically beneficial for disease states in which fever can be fatal, particularly for those fevers having fast onset. For example, patients undergoing chimeric antigen receptor T-cell (CAR-T) therapy may suffer fevers caused by cytokine release syndrome (CRS). Accordingly, a continuous temperature monitor is used to collect temperature data from CAR-T patients with high risk of CRS (or like patients with high fever risk), and the collected temperature data processed by a machine learning system to predict the patient's future temperature profiles. Results of analysis of the predicted temperature profiles may then be provided to the patient and/or clinician.