Deployable dashboard for ICU models

Abstract

Health care systems all around the world have an ever-growing burden of intensive care on them. Complications such as sepsis, organ failure and shock contribute to a large portion of the deaths. However they can be treated as long as they are detected early. Machine learning and artificial intelligence models for prediction of such conditions have been proven effective. This project aims at building a real world deployable dashboard that will help in evaluation and iterative learning of the models with a doctor in the loop. This dashboard is a human centric platform that will enable the evaluation of the models on a daily basis and help the doctors with monitoring and treatment of the patients. The work done in the project involves automation of the data feeding process and building a deployable dashboard that can be used to gain real-time feedback from the users.