Information Model of Outdoor Air Pollution Prediction for Medical Diagnosis System

Abstract

Medical diagnosis system needs prediction data on concentration of air pollutants to support making of personal decisions about outdoor activities for a day. It should extend decision made by doctor concerning medical diagnosis to decisions made by patient. Information model of outdoor air pollution prediction was presented. Information model is based on prediction model which was created and trained for prediction of nitrogen dioxide concentration. Prediction model was created using recurrent neural network based on long short term memory architecture. Experimental investigation was performed using dataset collected in Madrid during period from 2001 to 2020. Experimental investigation approved efficiency of the developed model. The created information model was developed as separate module of nitrogen dioxide concentration prediction inside medical diagnosis system.