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

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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Bibliographic Details
Main Authors: Thomas Birk Kristiansen, Kent Kristensen, Jakob Uffelmann, Ivan Brandslund
Format: Article
Language:English
Published: Frontiers Media S.A. 2022-07-01
Series:Frontiers in Digital Health
Subjects:
AI
artificial intelligence
data quality
personalized medicine
machine learning (ML)
deep learning
Online Access:https://www.frontiersin.org/articles/10.3389/fdgth.2022.862095/full

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https://www.frontiersin.org/articles/10.3389/fdgth.2022.862095/full

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