Tackling algorithmic bias and promoting transparency in health datasets: the STANDING Together consensus recommendations

Alderman, Joseph E; Palmer, Joanne; Laws, Elinor; McCradden, Melissa D; Ordish, Johan; Ghassemi, Marzyeh; Pfohl, Stephen R; Rostamzadeh, Negar; Cole-Lewis, Heather; Glocker, Ben; Calvert, Melanie; Pollard, Tom J; Gill, Jaspret; Gath, Jacqui; Adebajo, Adewale; Beng, Jude; Leung, Cassandra H; Kuku, Stephanie; Farmer, Lesley-Anne; Matin, Rubeta N; Mateen, Bilal A; McKay, Francis; Heller, Katherine; Karthikesalingam, Alan; Treanor, Darren; Mackintosh, Maxine; Oakden-Rayner, Lauren; Pearson, Russell; Manrai, Arjun K; Myles, Puja; Kumuthini, Judit; Kapacee, Zoher; Sebire, Neil J; Nazer, Lama H; Seah, Jarrel; Akbari, Ashley; Berman, Lew; Gichoya, Judy W; Righetto, Lorenzo; Samuel, Diana; Wasswa, William; Charalambides, Maria; Arora, Anmol; Pujari, Sameer; Summers, Charlotte; Sapey, Elizabeth; Wilkinson, Sharon; Thakker, Vishal; Denniston, Alastair; Liu, Xiaoxuan

doi:10.1016/s2589-7500(24)00224-3

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Tackling algorithmic bias and promoting transparency in health datasets: the STANDING Together consensus recommendations

Joseph E Alderman, Joanne Palmer, Elinor Laws, Melissa D McCradden, Johan Ordish, Marzyeh Ghassemi, Stephen R Pfohl, Negar Rostamzadeh, Heather Cole-Lewis, Ben Glocker, Melanie Calvert, Tom J Pollard, Jaspret Gill, Jacqui Gath, Adewale Adebajo, Jude Beng, Cassandra H Leung, Stephanie Kuku, Lesley-Anne Farmer, Rubeta N Matin, Bilal A Mateen, Francis McKay, Katherine Heller, Alan Karthikesalingam, Darren Treanor, Maxine Mackintosh, Lauren Oakden-Rayner, Russell Pearson, Arjun K Manrai, Puja Myles, Judit Kumuthini, Zoher Kapacee, Neil J Sebire, Lama H Nazer, Jarrel Seah, Ashley Akbari

, Lew Berman, Judy W Gichoya, Lorenzo Righetto, Diana Samuel, William Wasswa, Maria Charalambides, Anmol Arora, Sameer Pujari, Charlotte Summers, Elizabeth Sapey, Sharon Wilkinson, Vishal Thakker, Alastair Denniston, Xiaoxuan Liu

The Lancet Digital Health, Volume: 7, Issue: 1, Pages: e64 - e88

Swansea University Author: Ashley Akbari

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DOI (Published version): 10.1016/s2589-7500(24)00224-3

Published in:	The Lancet Digital Health
ISSN:	2589-7500
Published:	Elsevier BV 2025
Online Access:	Check full text
URI:	https://cronfa.swan.ac.uk/Record/cronfa68621

College:	Faculty of Medicine, Health and Life Sciences
Funders:	STANDING Together was funded by The NHS AI Lab and The Health Foundation and was supported by the National Institute for Health and Care Research (NIHR; AI_HI200014).
Issue:	1
Start Page:	e64
End Page:	e88

Tackling algorithmic bias and promoting transparency in health datasets: the STANDING Together consensus recommendations

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