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More than just sound: Harnessing metadata to improve neural network classifiers for medical auscultation
Label-efficient algorithms are of central importance for machine learning applications in many medical fields, where obtaining expert annotations is often expensive and time-consuming. Soni et al. show how contrastive learning can help build classifiers for one of the oldest and most revered methods...
Autor principal: | Matek, Christian |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8767290/ https://www.ncbi.nlm.nih.gov/pubmed/35079721 http://dx.doi.org/10.1016/j.patter.2021.100426 |
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