Thursday, Oct 6, 2022
Outsmarting Infectious Diseases with a Blend of Artificial Intelligence and Medicine
Dr. Anasse Bari, Professor of Computer Science - Director of the AI and Predictive Analytics Lab, New York University
Prof. Dr. Steffen Wagner, Lead Data Scientist, INWT Statistics
In January 2020, just after the first case of COVID-19 was discovered in the US, a multidisciplinary team of AI and medicine experts both in the US and China developed the first COVID-19 Clinical Severity Predictive Analytics Tool. In July 2021, another tool named COVID-19 Early-alerts Signals was built on a digital epidemiology framework that analyses alternative data sources to discover predictors of the pandemic curve. After the vaccine rollout, another team also co-led by the speaker developed a Vaccine Hesitancy Analytics Tool which is a real-time big data analytics cloud application to track misinformation and extract themes and topics related to vaccine hesitancy. In this keynote, Prof. Bari will outline the experimental research results from the three studies and the tools his team developed at New York University. This talk will also cover how governments and health systems can detect and respond to outbreaks, and how they can prepare for future pandemics using predictive analytics, mature AI capabilities, and infectious disease knowledge.