Sepsis contributes to as many as 50% of hospital deaths. A new tool developed by Johns Hopkins engineer and ICM core faculty member, Suchi Saria, could help doctors spot sepsis before it’s too late. Saria was featured in NovaNext for her extensive work using computer algorithms and patient data to save lives.

“The signs that help pinpoint the diagnosis may already be in your data, but the data in electronic medical records are really messy,” Saria says. “We’re designing computer algorithms based on statistical and computational techniques that were recently developed to allow clinical experts to identify sepsis faster.”

Read the full article, “Using Artificial Intelligence to Spot Hospitals’ Silent Killer” here.