Session ID: 

Lessons from Israel: Finding Cancers with AI and EHR Data

10:00am - 11:00am Wednesday, February 13
Orlando - Orange County Convention Center


What can the U.S. health system learn from its Israeli counterpart when it comes to leveraging existing EHR data for preventative care? Israel’s digital database (the world’s second largest) has collected medical records for over 98% of the population to further the development of preventative treatment and personalized care plans. In this session, the speaker goes beyond conjecture to demonstrate how U.S. health systems can learn from the Israeli model and integrate AI tools into clinical practice to identify high-risk patients and create a clinical path for effective intervention. She will reference the real-world development, validation, implementation, adoption and results of an AI-based tool designed to flag individuals at risk of harboring colorectal cancer using only existing EHR data. The clinical and ROI results of this implementation will reveal how AI can facilitate early interventions to improve patient outcomes while enabling health systems to prioritize resources.

Learning Objectives: 

  • Demonstrate how the U.S. health system can learn from Israel’s approach to digital health and the use of existing EHR data
  • Discuss clinical and ROI results of a real-world, machine-learning case study that used only blood count results and demographics to successfully detect individuals at risk of cancer
  • Identify the processes necessary for a streamlined and simple AI implementation, aligned with clinical workflow, to support an effective patient-centric health system


Director, Institute of Research and Innovation ,
Maccabitech, Maccabi Health Services


Clinical Informaticists
Government or Public Policy Professional
Population Health Management Professional