Generalising from conventional pipelines using deep learning in high-throughput screening workflows
Abstract The study of complex diseases relies on large amounts of data to build models toward precision medicine. Such data acquisition is feasible in the context of high-throughput screening, in which the quality of the results relies on the accuracy of the image analysis. Although state-of-the-art...
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| Autores principales: | , , , , , , , , , , |
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| Formato: | Artigo |
| Lenguaje: | Inglês |
| Publicado: |
Nature Portfolio
2022-07-01
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| Colección: | Scientific Reports |
| Acceso en línea: | https://doi.org/10.1038/s41598-022-15623-7 |
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