Innovators Under 35
INNOVATIVE Humanitarians
H2. Suchi Saria, 34
Johns
Hopkins University
Putting existing medical data to work
to predict sepsis risk.
Problem: Sometimes
the difference between life and death is a quick and accurate diagnosis. With
sepsis, a life-threatening reaction to an infection, there’s no definitive
single test doctors can use to diagnose the condition.
Solution: Suchi Saria, an
assistant professor at Johns Hopkins University, wondered: what if existing
medical information could be used to predict which patients would be most at
risk for sepsis? Algorithms that she subsequently created to analyze patient data
correctly predicted septic shock in 85 percent of cases, by an average of more
than a day before onset. That is a 60 percent improvement over existing
screening tests.
—Emily Mullin
—Emily Mullin
MIT TECHNOLOGY REVIEW
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