PREDICTIVE HEALTH MODEL FOR IDF MEDICAL CORPS 

Three researchers from the Digital Medical Technology department received an important two-year grant from the Chief Medical Officer of the IDF.

Dr. Refael Barkan, Dr. Hadas Lewy and Dr. Tomas Karpati received this grant in order to create a predictive model of abnormal morbidity among solders serving in the IDF. Morbidity refers to a disease, or symptom of a disease, that manifests itself in an individual. This particular study will focus on inflammatory bowel disease and unbalanced lung disease among IDF soldiers who are at risk for complications. The aim of the research is to alert the Medical Corps of potential dangers ‘in real time’ of cases requiring intervention. 

The predictive model will employ state-of-the-art methods of machine learning and deep learning, based on the medical data provided about the IDF soldiers’ medical history. Building a predictive model in the world of medicine in general and for clinical needs in particular, is at the forefront of innovative health informatics and aims to optimize the quality of care, preparedness for medical intervention and prevention of further health deterioration.

The principle investigators for this research are:

Dr. Refael Barkan - Vice President of Innovation, Entrepreneurship and Internationalization; MD/PHD in Neurology and Computer Science, with experience in developing smart systems for managing complex patients.

Dr. Hadas Lewy - Head of Digital Health Ventures; leads R&D projects in the field of Digital Medicine, including smart data-based systems, disease management platforms and development of products on the basis of organizational knowledge.

Dr. Tomas Karpati - Director of the Health Informatics Laboratory, with a 20-year background in developing predictive models and personalized medicine.