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Titel:

Weighing the benefits and risks of collecting race and ethnicity data in clinical settings for medical artificial intelligence.

Dokumenttyp:
Journal Article; Review; Research Support, N.I.H., Extramural; Research Support, Non-U.S. Gov't
Autor(en):
Fiske, Amelia; Blacker, Sarah; Geneviève, Lester Darryl; Willem, Theresa; Fritzsche, Marie-Christine; Buyx, Alena; Celi, Leo Anthony; McLennan, Stuart
Abstract:
Many countries around the world do not collect race and ethnicity data in clinical settings. Without such identified data, it is difficult to identify biases in the training data or output of a given artificial intelligence (AI) algorithm, and to work towards medical AI tools that do not exclude or further harm marginalised groups. However, the collection of these data also poses specific risks to racially minoritised populations and other marginalised groups. This Viewpoint weighs the risks of...     »
Zeitschriftentitel:
Lancet Digit. Health
Jahr:
2025
Band / Volume:
7
Heft / Issue:
4
Seitenangaben Beitrag:
e286-e294
Volltext / DOI:
doi:10.1016/j.landig.2025.01.003
PubMed:
http://view.ncbi.nlm.nih.gov/pubmed/40148011
TUM Einrichtung:
Institut für Geschichte und Ethik der Medizin (Prof. Buyx)
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