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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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| Gepubliceerd in: | IEEE J Biomed Health Inform |
|---|---|
| Hoofdauteurs: | , , , , |
| Formaat: | Artigo |
| Taal: | Inglês |
| Gepubliceerd in: |
2018
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| Onderwerpen: | |
| Online toegang: | 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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