The Subset Seekers

Mar 11, 2022

10:00am – 11:00am CT

As Dr. Brian Garibaldi directed the Johns Hopkins Biocontainment Unit in Baltimore amid COVID-19, a fit, active man in his 30s struggled on a ventilator for 40 days. Meanwhile, a 117-year-old French nun contracted the disease, fully recovered and didn’t even know she had it. To explain this shocking difference, Garibaldi and Johns Hopkins Applied Physics Laboratory researchers Will Gray Roncal and Karla Gray Roncal leveraged big data and machine learning to unravel the mystery of the different reactions, predict patients’ probable disease course and identify unique treatment needs. Garibaldi, Will Gray Roncal and Karla Gray Roncal will discuss how big data and machine learning advanced precision medicine for COVID-19 and how the techniques could be applied to other diseases.

Programming descriptions are generated by participants and do not necessarily reflect the opinions of SXSW.

Karla Gray Roncal

Johns Hopkins University Applied Physics Laboratory

Will Gray Roncal

Johns Hopkins University Applied Physics Laboratory

Matthew Robinson

Johns Hopkins University School of Medicine

This event will be available online

Details

Primary Entry:
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SXSW Online
Format:

Panel

Type:

Session

Track:

Health & MedTech track sponsored by Optum

Level:

Advanced