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Can Machine Learning Be Better than Biased Readers?
Background: Training machine learning (ML) models in medical imaging requires large amounts of labeled data. To minimize labeling workload, it is common to divide training data among multiple readers for separate annotation without consensus and then combine the labeled data for training a ML model....
| Autores principales: | , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
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MDPI
2023
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10204355/ https://www.ncbi.nlm.nih.gov/pubmed/37218934 http://dx.doi.org/10.3390/tomography9030074 |