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Predicting Classifier Performance with Limited Training Data: Applications to Computer-Aided Diagnosis in Breast and Prostate Cancer
Clinical trials increasingly employ medical imaging data in conjunction with supervised classifiers, where the latter require large amounts of training data to accurately model the system. Yet, a classifier selected at the start of the trial based on smaller and more accessible datasets may yield in...
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| Gepubliceerd in: | PLoS One |
|---|---|
| Hoofdauteurs: | , , |
| Formaat: | Artigo |
| Taal: | Inglês |
| Gepubliceerd in: |
Public Library of Science
2015
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| Onderwerpen: | |
| Online toegang: | https://ncbi.nlm.nih.gov/pmc/articles/PMC4436385/ https://ncbi.nlm.nih.gov/pubmed/25993029 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1371/journal.pone.0117900 |
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