Date of Award
January 2023
Document Type
Open Access Thesis
Degree Name
Master of Public Health (MPH)
Department
School of Public Health
First Advisor
Richard Taylor
Second Advisor
Ambrose Wong
Abstract
Machine-Learning (ML) algorithms are increasingly used to assist clinicians in decision-making. Recent studies have shown, however, that machine learn- ing algorithms might be prone to unfairness, albeit unintentional. As such, it is important to ensure that algorithms do not discriminate against certain groups. This thesis examines an in-house algorithm used to predict agitation among mental-health patients in the emergency department and addresses biases that might arise from generated predictions.
Recommended Citation
Pang, William, "Ai Fairness: Assessment For Prediction Of Agitation In Mental Health Patients At Emergency Rooms" (2023). Public Health Theses. 2320.
https://elischolar.library.yale.edu/ysphtdl/2320
This Article is Open Access
Comments
This is an Open Access Thesis.