74 citations · 158 across the 9 of their papers we have counts for
9 papers
Predicting High-Flow Nasal Cannula Failure in an ICU Using a Recurrent Neural Network with Transfer Learning and Input Data Perseveration: A Retrospective Analysis
George A. Pappy, Melissa D. Aczon, Randall C. Wetzel +1
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. Time…
Improving Recurrent Neural Network Responsiveness to Acute Clinical Events
David Ledbetter, Eugene Laksana, Melissa Aczon +1
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…
Interpreting a Recurrent Neural Network's Predictions of ICU Mortality Risk
Long V. Ho, Melissa D. Aczon, David Ledbetter +1
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. A…
The Impact of Extraneous Variables on the Performance of Recurrent Neural Network Models in Clinical Tasks
Eugene Laksana, Melissa Aczon, Long Ho +3
Electronic Medical Records (EMR) are a rich source of patient information, including measurements reflecting physiologic signs and administered therapies. Identifying which variabl…
Predicting Individual Responses to Vasoactive Medications in Children with Septic Shock
Nicole Fronda, Jessica Asencio, Cameron Carlin +4
Objective: Predict individual septic children's personalized physiologic responses to vasoactive titrations by training a Recurrent Neural Network (RNN) using EMR data. Materials a…
Predicting Individual Physiologically Acceptable States for Discharge from a Pediatric Intensive Care Unit
Cameron Carlin, Long Van Ho, David Ledbetter +2
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…