Blood infections are one of the leading causes of morbidity and mortality worldwide, but researchers at Tel Aviv University have developed a new AI-driven technology to help identify patients who are at risk of serious illness as a result of blood infections.
Using the EHRs of roughly 8,000 patients at Tel Aviv’s Ichilov Hospital who had developed blood infections, the researchers trained the tool to review data including demographic specifics, blood test results, and overall medical history. After studying each patient’s data and medical history, the program was able to automatically identify medical files’ risk factors with an accuracy of 82%. According to the researchers, in the future this model could even serve as an early warning system for doctors, by enabling them to rank patients based on their risk of serious disease.
“We worked with the medical files of about 8,000 Ichilov Hospital patients who were found to be positive for blood infections between the years 2014 and 2020, during their hospitalization and up to 30 days after, whether the patient died or not,” explained Prof. Noam Shomron in a statement. “We entered the medical files into software based on artificial intelligence; we wanted to see if the AI would identify patterns of information 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.”
In their report published in the journal Scientific Reports, the team explained that “(b)loodstream infections (BSI) can lead to prolonged hospital stays, and life-threatening and aggressive complications, in addition to high costs to health care systems. . . . (T)imely and critical assessment of available microbiology results are necessary to ensure that individuals with BSI receive prompt, effective, and targeted treatment, for optimal clinical outcomes. However, the current standard-of-care, which mostly depends on blood culture-based diagnosis, is often extremely slow.”
Most of the time, the researchers continued, the blood system is a sterile one, but infection with a bacterium or fungus can occur during surgery, or as the result of complications from other infections, such as pneumonia or meningitis. The diagnosis of infection is made by taking a blood culture and transferring it to a growth medium for bacteria and fungi. The body’s immunological response to the infection can cause sepsis or shock, dangerous conditions that have high mortality rates.
“Using artificial intelligence, the algorithm was able to find patterns that surprised us, parameters in the blood that we hadn’t even thought about taking into account,” sais Prof. Shomron. “We are now working with medical staff to understand how this information can be used to rank patients in terms of the severity of the infection. We can use the software to help doctors detect the patients who are at maximum risk.”
Since the study’s success, Ramot, Tel Aviv University's technology transfer company, is working to register a global patent for the groundbreaking technology.
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