Predicting High-Flow Nasal Cannula Failure in an ICU Using a Recurrent Neural Network with Transfer Learning and Input Data Perseveration: A Retrospective Analysis

no code implementations • 20 Nov 2021 • George A. Pappy, Melissa D. Aczon, Randall C. Wetzel, David R. Ledbetter

The LSTM models trained with transfer learning generally performed better than the LR models, with the best LSTM model achieving an AUROC of 0. 78, vs 0. 66 for the LR, two hours after initiation.

Specificity Transfer Learning

Phenotyping of Clinical Time Series with LSTM Recurrent Neural Networks

no code implementations • 26 Oct 2015 • Zachary C. Lipton, David C. Kale, Randall C. Wetzel

We present a novel application of LSTM recurrent neural networks to multilabel classification of diagnoses given variable-length time series of clinical measurements.

General Classification Time Series +1