December 2021: Shomron, Zoabi and Lahav: AI predicts patients at risk of serious disease
Prof. Noam Shomron, Edmond J. Safra member, Yazeed Zoabi, Edmond J. Safra PhD fellow and Dan Lahav, Edmond J. Safra MSc fellow, used machine learning to identify patients at risk of serious illness as a result of bloodstream infections.
Prof. Noam Shomron, Edmond J. Safra member, and his students, Yazeed Zoabi, Edmond J. Safra PhD fellow and Dan Lahav, Edmond J. Safra MSc fellow (Medicine) used machine learning to identify patients at risk of serious illness as a result of bloodstream infections.
In collaboration with Dr. Ahuva Weiss Meilik, Prof. Amos Adler and Dr. Orli Kehat (Tel Aviv Sourasky Medical Center), the researchers trained machine learning algorithms on electronic medical records of about 8,000 patients with bloodstream infections. They were able to identify patients at risk of poor outcomes with an accuracy (AUC) of 82%. The model can serve as an early-warning system for doctors, enabling them to rank patients based on their risk of developing serious disease. The study was published in
Ramot, the technology transfer company of Tel Aviv University, is working to register a global patent for the technology.
Read more here: JNS, TIMES OF ISRAEL, ISRAEL365NEWS, JEWISHPRESS.
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