Tal Alon and Yarden Shapira are students in the Lapidim excellence program at the Faculty of Computer Science. They developed an innovative information management system for the Galilee Medical Center that is designed to help hospital administrators make educated, evidence-based decisions during emergency situations.
The two students were supervised by Prof. Benny Kimelfeld, academic director of the Lapidim program. The system they developed features a user-friendly display of all the critical data the hospital administration needs to make decisions in real time.
These include the number of people in each department, the expected number of hospitalizations and discharges, and the availability of operating rooms and blood units.
Without this system, the medical teams would have to specifically request this information from the IT staff at the hospital, but now this essential, comprehensive data is provided quickly and automatically to facilitate faster and more efficient treatment. The system was used during a war drill at the hospital and proved effective.
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A new article published by scholars at the Taub Faculty of Computer Science at the Technion – third-year student Shunit Agmon and Dr. Kira Radinsky, in conjunction with Dr. Eric Horowitz from Microsoft Research, presents a specific bias that impacts the application of the findings of clinical trials, namely the underrepresentation of women in clinical research.
The article, published in the Journal of the American Medical Informatics Association (JAMIA), describes this bias and presents specific tools for mitigating its effects and improving healthcare for women. The researchers addressed the problem using tools and technologies from the world of machine learning, including natural language processing (NLP) and word embeddings, to enable the computer to “understand” text.
The algorithm they developed significantly improved the ability to predict various aspects of healthcare for women, including length of hospitalization, re-admission within a month of discharge, and correlations between illnesses. The researchers believe that their publication will increase awareness of the problems caused by underrepresentation in clinical trials and in research in general, and facilitate the development of new solutions for improving customized healthcare.
Technion students Elinor Ginzburg, Leon Kosarev, and Tomer Ron worked with the neurosurgical department at Rambam Hospital to develop a system that alerts the medical staff when a patient attempts to get out of bed.
Elinor discovered the problem of patients falling while volunteering in hospitals. This is a problem that has been researched in hospitals worldwide and is considered a major challenge. When patients are left alone in their hospital beds, the medical team lifts the bedrail to prevent patients from trying to get up without assistance.
However, despite the bedrails, many patients try to climb over the bedrail and get out of bed. This often results in falls, longer recovery time, and severe injuries.
The project was developed as part of an IoT course and was led by Itai Dabran and Tom Sofer, engineers from the Interdisciplinary Center for Smart Technologies (ICST) who work with their students to develop products and technologies designed to contribute to society.
Photos from a fair in June 2022 in which IoT-Android, Arduino, and network projects were presented.
