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Bias and Discrimination in AI

Présenté par

Université de Montréal

Dès le 10 novembre 2020
En ligne

Activités de formation

Algorithms and the data they process play an increasingly important role in decisions with important consequences for human well-being.
While algorithmic decision-making can lead to fairer and more objective decisions, new research suggests that they can also lead to unequal and inequitable treatment and outcomes for certain groups or individuals.
 

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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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