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*4th PLACE* of our most impactful articles published in @RSeriesa in 2020 according to @altmetric:

Tanner et al: doi.org/10.1111/rssa.1โ€ฆ

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*CONTEXT* Dynamic prediction models provide predicted probabilities that can be updated over time as data become available. There is growing interest in the use of #machinelearning ๐Ÿค–; yet, their use in the context of dynamic survival #prediction has been limited.
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*AIM* Show how #landmarking can be combined with a #machinelearning ensemble to improve prediction performance

*METHOD* Use of discrete time #survivalanalysis techniques to enable the use of #machinelearning algorithms for binary outcomes
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