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AI technology helps identify patients at risk from sepsis

A new artificial intelligence technology developed at Tel Aviv University will make it possible to identify patients at risk of serious illness from blood infections – one of the world’s leading causes of morbidity and mortality.

Researchers trained the AI program to examine the electronic medical records of approximately 8,000 patients at Tel Aviv Sourasky Medical Center who were found positive for blood infections between 2014 and 2020. These records included demographics, blood test results, medical history, and diagnosis.

“We wanted to see if the AI could see information patterns in the files that would allow us to automatically predict which patients would develop serious illness or even death as a result of the infection,” explains Prof. Noam Shomron.

The program automatically identified risk factors with an accuracy of 82 percent.

“The algorithm was able to use artificial intelligence to find patterns that surprised us, parameters in our blood that we hadn’t even thought of,” says Shomron.

“We are now working with healthcare professionals to understand how this information can be used to grade patients according to the severity of the infection. We can use the software to help doctors identify the patients who are at maximum risk. “

While the blood system is usually sterile, infection can occur during surgery or as a result of complications from other infections such as pneumonia or meningitis. The body’s immunological response to the blood infection can cause sepsis or shock, dangerous conditions that can lead to organ failure and even death.

Results of the study were released in the diary Scientific reports by a team from Shomron’s Genomics Lab and colleagues from the medical center.

Ramot, Tel Aviv University’s technology transfer company, is working to apply for a worldwide patent for the breakthrough technology.

Keren Primor Cohen, CEO of Ramot said, “Ramot believes in the ability of this innovative technology to make a significant difference in the early detection of patients at risk and help hospitals cut costs. This is an example of effective collaboration between university researchers and hospitals that improves the quality of medical care in Israel and around the world. “