Towards a Complex Evolutionary Agent-Based System for Medical Sensor Data

Various gadgets and medical devices collect data from patients continuously. Processing this information and learning from it is a challenge for data scientists as this kind of data comes in complex and large quantities, making the decision of what kind of algorithms to apply for the best results difficult and time consuming. In this paper we propose a Multi-agent system that enables autonomous selection and application of machine learning methods for data sets belonging to medical systems, by applying genetic algorithms to agents.