Contact: tsbevents@itu.int

Introduction
The AI Summit Health breakthrough track acted as the Focus Group on AI for Health’s (FG-AI4H) 5th Workshop.                   
     
The session framed the AI4H breakthrough by providing an overview of the activities of the Focus Group on AI for Health, which came out of the 2018 Health breakthrough track, and the topics and aspects that the Focus Group and breakthrough chairs would like to address including opportunities for standardization of AI solutions for health. It highlighted how AI and machine learning revolutionarized healthcare in the areas of clinical decision support, personalized medicine, augmented diagnosis capabilities, medical imaging interpretation, therapeutic purposes and disease prevention. The session provided an overview of the process and methodology of benchmarking AI algorithms for health, along with approaches and challenges to algorithms assessment. It discussed how standardization process could lead to responsible adoption of algorithmic decision-making tools and to improve the accuracy of the algorithms. It described the proposal of a highly available system/ infrastructure for benchmarking the algorithms.

Objectives

• Identify standardization opportunities for a benchmarking framework that will enable the broad adoption of AI for health (AI4H).
• Process to apply the benchmark dataset for testing new algorithms.
• What are different types of benchmarking we want to do.
• How to set-up an open source testing infrastructure that will allow 24h testing system to operate.