The Focus Group on Artificial Intelligence for Health (FG-AI4H) is a partnership of ITU and the World Health Organization (WHO) to establish a standardized assessment framework for the evaluation of AI-based methods for health, diagnosis, triage or treatment decisions. Participation in the FG-AI4H is free and open to all. The group was established by ITU-T Study Group 16 at its meeting in Ljubljana, Slovenia, 9-20 July 2018 and closed operations on 30 September 2023. Its work is grandfathered in the Global Initiative on AI for Health (GI-AI4H)
launched by ITU, WHO and WIPO on 5 July 2023 during the AI for Good Summit.
The FG scope and general process were described in a
commentary in The Lancet and a
white paper. The documentation of all previous meetings can be found on the
collaboration site (free
ITU account needed; see
instructions for help). Learn more about the FG operations in the
Terms of reference Parent group > ITU-T Study Group 16
The 35 FG-AI4H deliverables
follow four pillars on AI for health: (1) ethics, (2) regulations, (3) technology and (4) clinical evaluation and use cases. It also produced other outputs tailored to specific needs. Here are some of them:
Access all completed deliverables
Topic groups (TGs) investigate use cases within specific health domains with corresponding AI/ML tasks. Currently there are 24 groups, three of which are starting their activities.
More >Working Groups
Working groups (WGs) consider crosscutting subject matters that affect a specific aspect of an AI health application.
Open Code Initiative
The Open Code Initiative worked to implement the building blocks of the FG-AI4H assessment platform as a digital public good, which will support the end-to-end assessment of AI for health algorithms under consideration of regulatory guidelines and the needs of all AI for health stakeholders.
More >OCI development site |
Terms of reference
Ad-hoc Group on Digital Technologies for COVID Health Emergencies
reviews the role of AI (and other digital technologies) in combatting COVID-19 throughout an epidemic’s life cycle. Through this case study, we will learn how to best leverage digital technologies to successfully manage future health emergencies.
Other output documents
Q-102: Updated call for proposals: use cases, benchmarking, and data
F-103: Updated FG-AI4H data acceptance and handling policy
C-104: Thematic classification scheme
F-105: ToRs for the WG-Experts and call for experts
F-106: Guidelines on FG-AI4H online collaboration tools
M-107: Onboarding FG-AI4H document
updates and announcements
to the FG-AI4H mailing list (see the "Participating" tab on the right of this page).