Blood infections are one of the leading causes of morbidity and mortality in the world. The body’s immunological response to the infection can cause sepsis or shock, dangerous conditions that have high mortality rates. Thus, it is very important to identify the risk factors for developing serious illness at the early stage of infection. A new technology developed at Tel Aviv University will make it possible, using artificial intelligence (AI), to identify patients who are at risk of serious illness as a result of blood infections.

The researchers trained the AI program to study the medical records of about 8,000 patients at Tel Aviv’s Ichilov Hospital who were found to be positive for blood infections. These records included demographic data, blood test results, medical history and diagnosis. After studying each patient’s data and medical history, the program was able to automatically identify patients at risk of serious illness with an accuracy of 82%, even when ignoring obvious factors such as the age of the patients and the number of hospitalizations they had endured. According to the researchers, in the future this model could even serve as an early warning system for doctors.

Potential to Save Many Lives

Behind this groundbreaking research, with the potential to save many lives, are students Yazeed Zoabi and Dan Lahav from the laboratory of Prof. Noam Shomron of Tel Aviv University’s Sackler Faculty of Medicine, in collaboration with Dr. Ahuva Weiss Meilik, head of the I-Medata AI Center at Ichilov Hospital, Prof. Amos Adler, and Dr. Orli Kehat. The results of the study were published in the journal Scientific Reports.

“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,” explains Prof. Noam Shomron. “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.”

Cooperation between Researchers and Hospitals

“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,” says 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 Tech Transfer Company, is working to register a global patent for the groundbreaking technology. Keren Primor Cohen, CEO of Ramot, says, “Ramot believes in this innovative technology’s ability to bring about a significant change in the early identification of patients at risk and help hospitals reduce costs. This is an example of effective cooperation between the university’s researchers and hospitals, which improves the quality of medical care in Israel and around the world.”

Featured image: Prof. Noam Shomron (Photo: Corinna Kern)