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Synthetic Data for Health Symposium

Présenté par

IVADO

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Activités de formation

AI algorithms and intelligent systems hold great promise in the health sector, such as decreasing the cost of supporting an aging population, discovering new therapeutic avenues for complex disease such as cancers, and better patient management. To support future advances in the Canadian healthcare system with data intelligent algorithms, barriers to data access and privacy must be addressed, and many scientists are turning toward generative models and synthetic datasets for innovative solutions.

This symposium is hosted by CIFAR in partnership with IVADO and Mila.

Activities

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Featured project

Intraoperative analgesic treatment decisions based on the NOL index: contribution of a data-based approach to improve accuracy and relevance

Student member : Marzieh Ghiyasinasab

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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