65 citations · 221 across the 19 of their papers we have counts for
5 papers · 1 filter
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…
A Simple Modeling Framework For Prediction In The Human Glucose-Insulin System
M. Sirlanci, M. E. Levine, C. C. Low Wang +2
In this paper, we build a new, simple, and interpretable mathematical model to estimate and forecast physiology related to the human glucose-insulin system, constrained by availabl…
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…
Ensemble Kalman Methods With Constraints
David J. Albers, Paul-Adrien Blancquart, Matthew E. Levine +2
Ensemble Kalman methods constitute an increasingly important tool in both state and parameter estimation problems. Their popularity stems from the derivative-free nature of the met…