Vir Biotechnology Scientists Named Winners of the BARDA and HHS-Sponsored Pediatric COVID-19 Data Challenge
The contributing scientists were
Responding to the challenge, the Vir team employed a state-of-the-art machine learning model called the “missingness-aware gradient boosted tree classifier,” which assessed the risk of hospitalization and severe outcomes among pediatric patients by extracting patterns in both the data that were present and the observations that were absent.
“The tremendous volume of data generated during the pandemic provides significant opportunities for the development and implementation of predictive tools that can help anticipate critical care needs, optimize treatment for the highest risk patients and reduce COVID-19 morbidity and mortality,” said Dr. Telenti. “We were thrilled to successfully contribute to this challenge with our model and hope that these efforts will foster a new generation of decision support tools that will result in improved patient care and outcomes.”
“This award and acknowledgement from BARDA and HHS speak not only to the capabilities of our world-class scientists, but also to our leadership in developing and leveraging impactful artificial intelligence and machine learning technologies. We deploy these cutting-edge tools each day, as we work across our pipeline to better understand and treat infectious diseases,” said
The Pediatric COVID-19 Data Challenge award included a
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Source: Vir Biotechnology, Inc.