Analyzing the Role of Model Uncertainty for Electronic Health Records

10 Jun 2019Michael W. DusenberryDustin TranEdward ChoiJonas KempJeremy NixonGhassen JerfelKatherine HellerAndrew M. Dai

In medicine, both ethical and monetary costs of incorrect predictions can be significant, and the complexity of the problems often necessitates increasingly complex models. Recent work has shown that changing just the random seed is enough for otherwise well-tuned deep neural networks to vary in their individual predicted probabilities... (read more)

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