AI pitfalls and what not to do: mitigating bias in AI

Various forms of artificial intelligence (AI) applications are being deployed and used in many healthcare systems. As the use of these applications increases, we are learning the failures of these models and how they can perpetuate bias. With these new lessons, we need to prioritize bias evaluation...

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Detalles Bibliográficos
Autores principales: Gichoya, Judy Wawira, Thomas, Kaesha, Celi, Leo Anthony, Safdar, Nabile, Banerjee, Imon, Banja, John D, Seyyed-Kalantari, Laleh, Trivedi, Hari, Purkayastha, Saptarshi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: The British Institute of Radiology. 2023
Materias:
AI in imaging and therapy: innovations, ethics, and impact: Review Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10546443/
https://www.ncbi.nlm.nih.gov/pubmed/37698583
http://dx.doi.org/10.1259/bjr.20230023

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10546443/
https://www.ncbi.nlm.nih.gov/pubmed/37698583
http://dx.doi.org/10.1259/bjr.20230023

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