Machine Learning Controlled Self-Adaptive Plasma Medicine

Abstract

Cold atmospheric plasma (CAP) medicine is a novel technology of drug delivery that potentially has diverse applications including cancer treatment, tissue generation, sterilization, and blood coagulation1. Previously, we proposed an idea of self-adaptive plasma which can automatically optimize the plasma parameters such as reactive oxygen and nitrogen species (RONS) to immune the dynamic environmental disturbance and target status2,3. As the next step of self-adaptive plasma, a machine-learning based plasma control system is required.