4 citations · 6 across the 5 of their papers we have counts for
11 papers
A damaged-informed lung model for ventilator waveforms
Deepak. K. Agrawal, Bradford J. Smith, Peter D. Sottile +1
The acute respiratory distress syndrome (ARDS) is characterized by the acute development of diffuse alveolar damage (DAD) resulting in increased vascular permeability and decreased…
Delay-Induced Uncertainty for a Paradigmatic Glucose-Insulin Model
Bhargav Karamched, George Hripcsak, Dave Albers +1
Medical practice in the intensive care unit is based on the supposition that physiological systems such as the human glucose-insulin system are predictable. We demonstrate that del…
Using Data Assimilation of Mechanistic Models to Estimate Glucose and Insulin Metabolism
Jami J. Mulgrave, Matthew E. Levine, David J. Albers +3
Motivation: There is a growing need to integrate mechanistic models of biological processes with computational methods in healthcare in order to improve prediction. We apply data a…
Enabling Personalized Decision Support with Patient-Generated Data and Attributable Components
Elliot G Mitchell, Esteban G Tabak, Matthew E Levine +2
Decision-making related to health is complex. Machine learning (ML) and patient generated data can identify patterns and insights at the individual level, where human cognition fal…
Multi-Task Gaussian Processes and Dilated Convolutional Networks for Reconstruction of Reproductive Hormonal Dynamics
Iñigo Urteaga, Tristan Bertin, Theresa M. Hardy +2
We present an end-to-end statistical framework for personalized, accurate, and minimally invasive modeling of female reproductive hormonal patterns. Reconstructing and forecasting…
The Parameter Houlihan: a solution to high-throughput identifiability indeterminacy for brutally ill-posed problems
DJ Albers, M Levine, L Mamykina +1
One way to interject knowledge into clinically impactful forecasting is to use data assimilation, a nonlinear regression that projects data onto a mechanistic physiologic model, in…