Phenotyping of Clinical Time Series with LSTM Recurrent Neural Networks
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Abstract (arXiv)
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.
Key facts. Cited by 2 papers in the map (data through 14 Oct 2026). First posted on arXiv 26 Oct 2015.
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Citing papers per year: 2021: 1; 2022: 0; 2023: 1.
2 papers.