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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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| Publicado no: | IEEE J Biomed Health Inform |
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| Main Authors: | , , , , |
| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
2018
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| Assuntos: | |
| Acesso em linha: | 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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