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Accounting for Label Uncertainty in Machine Learning for Detection of Acute Respiratory Distress Syndrome

When training a machine learning algorithm for a supervised-learning task in some clinical applications, uncertainty in the correct labels of some patients may adversely affect the performance of the algorithm. For example, even clinical experts may have less confidence when assigning a medical diag...

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Dades bibliogràfiques
Publicat a:IEEE J Biomed Health Inform
Autors principals: Reamaroon, Narathip, Sjoding, Michael W., Lin, Kaiwen, Iwashyna, Theodore J., Najarian, Kayvan
Format: Artigo
Idioma:Inglês
Publicat: 2018
Matèries:
Accés en línia:https://ncbi.nlm.nih.gov/pmc/articles/PMC6351314/
https://ncbi.nlm.nih.gov/pubmed/29994592
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1109/JBHI.2018.2810820
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