Erroneous data: The Achilles' heel of AI and personalized medicine

This paper reviews dilemmas and implications of erroneous data for clinical implementation of AI. It is well-known that if erroneous and biased data are used to train AI, there is a risk of systematic error. However, even perfectly trained AI applications can produce faulty outputs if fed with erron...

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Detalles Bibliográficos
Autores principales: Kristiansen, Thomas Birk, Kristensen, Kent, Uffelmann, Jakob, Brandslund, Ivan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Digital Health
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9355416/
https://www.ncbi.nlm.nih.gov/pubmed/35937419
http://dx.doi.org/10.3389/fdgth.2022.862095

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9355416/
https://www.ncbi.nlm.nih.gov/pubmed/35937419
http://dx.doi.org/10.3389/fdgth.2022.862095

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