Artificial Intelligence for Public Health (AI4PH): A focus on equity and prevention

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July 13-14 and 20-21, 2021
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Activités de formation

Applications are now being accepted for an innovative training program, the Artificial Intelligence for Public Health (AI4PH) Summer Institute, that will be offered for the first time in 2021. A summer Institute funded by CIHR and developed by a pan-Canadian team of investigators and partners. Applicants accepted to attend the AI4PH Summer Institute will have the opportunity to expand their skills and knowledge related to the application of AI innovations in public health research and practice while exploring the potential impact of AI technologies on the widening or narrowing of health inequities.

Who can apply?
PhD students, post-doctoral fellows, and early-career investigators (within 5 years of their first appointment as an independent researcher) who seek to develop knowledge and skills in AI methods, public health applications, and the importance of an equity lens throughout the AI research process.

Applicants must be affiliated with a Canadian institution (e.g., university, college, health institute or agency).

Participants selected to participate in the AI4PH Summer Institute will benefit from a stimulating, interactive program that includes small-group discussions, tutorials, data challenge activities, and research talks. Participants will have the opportunity to:

  • Learn from a diverse group of leading researchers in public health and AI;
  • Network and collaborate with their peers, who will bring perspectives from public health, ethics, social sciences, and computational sciences;
  • Develop and refine their computational skills;
  • Explore state-of-the art public health data to build confidence in AI- and equity-focused analyses.



Featured project

This research project is based on the analysis of massive data on the NOL index and other intraoperative clinical parameters used by anesthesiologists during surgery. These parameters help them make analgesic treatment decisions in a non-communicating patient under general anesthesia and in whom it is impossible to assess pain and analgesic needs by standard questionnaires performed on awake patients. 
First, the objective is to interpret the values of this index in relation to the decisions made by the clinician. 

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