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Ziad Obermeyer

2 accepted papers

2019

Direct Uncertainty Prediction for Medical Second Opinions

ICML 2019oral

The issue of disagreements amongst human experts is a ubiquitous one in both machine learning and medicine. In medicine, this often corresponds to doctor disagreements on a patient diagnosis. In this work, we show that machine learning models can be successfully trained to give uncertainty scores to…

Cited by 171SourcePDFScholar
2019

Discriminative Regularization for Latent Variable Models with Applications to Electrocardiography

ICML 2019oral

Generative models often use latent variables to represent structured variation in high-dimensional data, such as images and medical waveforms. However, these latent variables may ignore subtle, yet meaningful features in the data. Some features may predict an outcome of interest (e.g. heart attack)…