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pro vyhledávání: '"Aczon, Melissa"'
High Flow Nasal Cannula (HFNC) provides non-invasive respiratory support for critically ill children who may tolerate it more readily than other Non-Invasive (NIV) techniques. Timely prediction of HFNC failure can provide an indication for increasing
Externí odkaz:
http://arxiv.org/abs/2111.11846
Predictive models in acute care settings must be able to immediately recognize precipitous changes in a patient's status when presented with data reflecting such changes. Recurrent neural networks (RNNs) have become common for training and deploying
Externí odkaz:
http://arxiv.org/abs/2007.14520
A novel application of spectrograms with machine learning can detect patient ventilator dyssynchrony
Autor:
Obeso, Ishmael, Yoon, Benjamin, Ledbetter, David, Aczon, Melissa, Laksana, Eugene, Zhou, Alice, Eckberg, R. Andrew, Mertan, Keith, Khemani, Robinder G., Wetzel, Randall
Publikováno v:
In Biomedical Signal Processing and Control September 2023 86 Part C
Deep learning has demonstrated success in many applications; however, their use in healthcare has been limited due to the lack of transparency into how they generate predictions. Algorithms such as Recurrent Neural Networks (RNNs) when applied to Ele
Externí odkaz:
http://arxiv.org/abs/1905.09865
Autor:
Laksana, Eugene, Aczon, Melissa, Ho, Long, Carlin, Cameron, Ledbetter, David, Wetzel, Randall
Electronic Medical Records (EMR) are a rich source of patient information, including measurements reflecting physiologic signs and administered therapies. Identifying which variables are useful in predicting clinical outcomes can be challenging. Adva
Externí odkaz:
http://arxiv.org/abs/1904.01125
Autor:
Fronda, Nicole, Asencio, Jessica, Carlin, Cameron, Ledbetter, David, Aczon, Melissa, Wetzel, Randall, Markovitz, Barry
Objective: Predict individual septic children's personalized physiologic responses to vasoactive titrations by training a Recurrent Neural Network (RNN) using EMR data. Materials and Methods: This study retrospectively analyzed EMR of patients admitt
Externí odkaz:
http://arxiv.org/abs/1901.10400
Objective: Predict patient-specific vitals deemed medically acceptable for discharge from a pediatric intensive care unit (ICU). Design: The means of each patient's hr, sbp and dbp measurements between their medical and physical discharge from the IC
Externí odkaz:
http://arxiv.org/abs/1712.06214
There is growing interest in applying machine learning methods to Electronic Medical Records (EMR). Across different institutions, however, EMR quality can vary widely. This work investigated the impact of this disparity on the performance of three a
Externí odkaz:
http://arxiv.org/abs/1703.08251
Akademický článek
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Publikováno v:
In Journal of Biomedical Informatics February 2021 114