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Tackling algorithmic bias and promoting transparency in health datasets: the STANDING Together consensus recommendations
2024
93 citations
Review
gold Open Access
Field-Weighted Citation Impact:
11.11
Tackling algorithmic bias and promoting transparency in health datasets: the STANDING Together consensus recommendations | Researchclopedia
Melanie Calvert
Tom Pollard
·
Massachusetts Institute of Technology
J. M. Gill
·
University Hospitals Birmingham NHS Foundation Trust
Jacqui Gath
Ade Adebajo
Jude Beng
·
University of Sheffield
Cheuk Wing Leung
Stephanie Kuku
·
London Women's Clinic
Lesley-Anne Farmer
Rubeta Matin
Bilal A. Mateen
Francis McKay
Katherine Heller
·
Google (United States)
Alan Karthikesalingam
·
Google (United Kingdom)
Darren Treanor
Maxine Mackintosh
Lauren Oakden‐Rayner
·
Australian Centre for Robotic Vision
Russell J. Pearson
Arjun K. Manrai
·
Harvard University
Puja Myles
Judit Kumuthini
·
University of Ibadan
Zoher Kapacee
·
Greater London Authority
Neil J. Sebire
Lama Nazer
·
King Hussein Cancer Center
Jarrel Seah
Ashley Akbari
Lewis E. Berman
Judy Wawira Gichoya
·
Emory University
Lorenzo Righetto
·
Springer Nature (United Kingdom)
D. V. K. Samuel
William Wasswa
·
Mbarara University of Science and Technology
Maria Charalambides
Anmol Arora
Sameer Pujari
·
World Health Organization
Charlotte Summers
·
Lung Institute
Elizabeth Sapey
S P Wilkinson
Vishal Thakker
·
British Standards Institution
Alastair K. Denniston
Xiaoxuan Liu