AI and Machine Learning in Health Programs

ICT4D Conference Webinar Series

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Resources featured in this webinar

​Artificial Intelligence (AI) has now moved from “hype” and “hope” to “results” and “impact” in its application for global health programs and health resilience initiatives. AI has the potential to prevent the spread of communicable diseases, extend aid and advocacy to remote regions, and deliver more targeted human-centric health services.

Mobile phones and other ICTs for data collection are already key components in public and emergency health programs. Adding algorithms and automation through machine learning and deep learning allows us to identify patterns in the data that can inform life-saving decisions.

This webinar is part of an ongoing series around ICT4D. It will explore, through an interactive discussion, how AI and machine learning tools can be applied and why they will play a key role in the achievement of the UN Sustainable Development Goals for Health and Nutrition. Attendees are encouraged to ask questions and join the debate.

Topics to be discussed include, but are not limited to:

  • Oversight: What new machine learning applications and systems are already available?
  • Case studies: What are the main use cases you see for AI in global health programs?
  • Addressing ethical considerations.
  • Lessons learned: what have we learnt from experience with AI tools so far?
  • What does the future hold?


Neil Sahota, United Nations AI Subject Matter Expert, Faculty at University of California, Irvine, and IBM Master Inventor

Steve Hellen, Director of ICT4D and GIS, Catholic Relief Services

Dr Anuraj Shankar, Senior Research Scientist, Harvard, T.H. Chan School of Public Health

Toby Norman, CEO, Simprints Technology


Sonja Ruetzel, ICT4D Partnerships & Conference Manager, Catholic Relief Services


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