Phenotyping of Clinical Time Series with LSTM Recurrent Neural Networks - Citegraph

Paper Info

Title
Phenotyping of Clinical Time Series with LSTM Recurrent Neural Networks

Abstract
We present a novel application of LSTM recurrent neural networks to multilabel classification of diagnoses given variable-length time series of clinical measurements. Our method outperforms a strong baseline on a variety of metrics.

Year	Venue	Field
2015	CoRR	Computer science,Recurrent neural network,Artificial intelligence,Machine learning,Medical diagnosis
DocType	Volume	Citations
Journal	abs/1510.07641	2
PageRank	References	Authors
0.37	12	3

Authors (3 rows)

Cited by (2 rows)

References (12 rows)

Name	Order	Citations	PageRank
Zachary Chase Lipton	1	534	45.49
David Kale	2	220	13.58
Randall C. Wetzel	3	182	11.24

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