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Temporal Convolutional Neural Networks for Diagnosis from Lab Tests
[article]
2016
arXiv
pre-print
Early diagnosis of treatable diseases is essential for improving healthcare, and many diseases' onsets are predictable from annual lab tests and their temporal trends. We introduce a multi-resolution convolutional neural network for early detection of multiple diseases from irregularly measured sparse lab values. Our novel architecture takes as input both an imputed version of the data and a binary observation matrix. For imputing the temporal sparse observations, we develop a flexible, fast to
arXiv:1511.07938v4
fatcat:sveroidxuzbnhgcys32vgtubg4