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Age-related bias and artificial intelligence: a scoping review
Charlene H. Chu
, Simon Donato-Woodger
, Shehroz S. Khan
, Rune Nyrup
,
Kathleen Leslie
, Alexandra Lyn
, Tianyu Shi
, Andria Bianchi
, Samira Abbasgholizadeh Rahimi
, Amanda Grenier
Faculty of Health Disciplines
University of Toronto
University of Cambridge
MacEwan University
McGill University
Mila - Quebec AI Institute
Jewish General Hospital
Research output
:
Contribution to journal
›
Review article
›
peer-review
56
Citations (Scopus)
Overview
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Keyphrases
Academic Search
25%
Age Recognition
25%
Age-related Bias
100%
Ageism
25%
Artificial Intelligence
100%
Artificial Intelligence Applications
25%
Artificial Intelligence Bias
25%
Artificial Intelligence Systems
75%
Artificial Intelligence Technology
25%
Bias in AI
25%
Comprehensive Search
25%
Convolutional Neural Network
25%
Digital Ageism
75%
Ethical Implications
50%
Evaluation Bias
25%
Facial Recognition System
25%
Inclusion Criteria
25%
Legal Implications
25%
Legal Sources
25%
Literature Search
25%
Machine Learning
25%
Machine Learning Algorithms
25%
Machine Learning Bias
25%
Representation Bias
25%
Scoping Review
100%
Search Strategy
25%
Social Bias
25%
Social Disparities
25%
Support Vector Machine
25%
Psychology
Ageism
44%
Artificial Intelligence
100%
Learning Algorithm
11%
Neural Network
11%
Scoping Review
100%