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Improving the repeatability of deep learning models with Monte Carlo dropout - npj Digital Medicine

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Improving the repeatability of deep learning models with Monte Carlo dropout - npj Digital Medicine

The integration of artificial intelligence into clinical workflows requires reliable and robust models. Repeatability is a key attribute of model robustness. Ideal repeatable models output predictions without variation during independent tests carried out under similar conditions. However, slight variations, though not ideal, may be unavoidable and acceptable in practice.

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Improving the repeatability of deep learning models with Monte Carlo dropout - npj Digital Medicine

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Improving the repeatability of deep learning models with Monte Carlo dropout - npj Digital Medicine

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