Why data storage, AI, cloud computing have been vital for COVID-19 research 

Medical researchers since March have been pivoting projects to focus on COVID-19, driving the critical need for machine learning and imaging analysis tools to support big data initiatives, according to a Nov. 13 Wall Street Journal report.

At the Center for Clinical Data Science, which is part of Boston-based Massachusetts General Hospital and Brigham and Women's Hospital, multidisciplinary teams with artificial intelligence skills have been vital for organizing and sifting through COVID-19 data sets.

"Many of us dropped all other research and tried to focus entirely on doing COVID modeling," Jayashree Kalpathy-Cramer, PhD, scientific director of the Center for Clinical Data Science, told the publication. The work required large amounts of data storage, easy access to data and enough computer power to build complex AI models.

Over the past several months, researchers from various MGH task forces have collaborated on AI algorithms in numerous ways, including using the models to predict which COVID-19 patients will require more advanced treatments and to identify how many intensive care unit beds could be needed at a particular time.

More articles on data analytics:
Centene acquires health data analytics company Apixio: 3 details
Microsoft-backed data alliance awards $1.2M for 3 cancer treatment innovation projects
El Paso's record COVID-19 numbers were inaccurate, health director expects more issues: 4 details

 

© Copyright ASC COMMUNICATIONS 2021. Interested in LINKING to or REPRINTING this content? View our policies by clicking here.

 

Featured Whitepapers

Featured Webinars