A seminar on AI, entitled "Predicting COVID-19 positivity and hospitalization with multi-scale graph neural networks", will take place on Thursday, March 3rd, 2022 at 11:00am at IHU Strasbourg, Hygie Room.
The speaker, Konstantinos Skianis, is the founder of BLUAI, a company focused on accelerating AI adoption and incorporating novel NLP technologies. He received his PhD from École Polytechnique under the supervision of Prof. Michalis Vazirgiannis and Prof. Guillaume Wisniewski. He has published in leading Machine Learning conferences and journals.
Abstract
The pandemic of COVID-19 is undoubtedly one of the biggest challenges for modern healthcare. From the beginning of the outbreak, new variants have also proven to be even more contagious, accelerating the spread and stressing the healthcare system. In order to analyze and understand the spatio-temporal spread of COVID-19, technology has helped us to track, identify and store information regarding positivity and hospitalization, across different levels of municipal entities. In this work, we present a method for predicting positive and hospitalized cases at the department level of France via a novel multi-scale graph neural network, integrating information from the IRIS level. Our model manages to outperform baselines and deep learning models, presenting low errors in both prediction tasks. We specifically point out the importance on predicting hospitalization and our contribution, since hospitals became critical infrastructure. To the best of our knowledge, this is the first work to exploit high-resolution spatio-temporal data in a multi-scale manner, incorporating additional knowledge, such as vaccination percentages and movement between areas. We believe that our method may improve future estimations of positivity and hospitalization, which is crucial for healthcare planning.
Virtual access to the seminar