121 citations · 133 across the 7 of their papers we have counts for
7 papers
Exploring approaches to computational representation and classification of user-generated meal logs
Guanlan Hu, Adit Anand, Pooja M. Desai +2
This study examined the use of machine learning and domain specific enrichment on patient generated health data, in the form of free text meal logs, to classify meals on alignment…
A new approach to data assimilation initialization problems with sparse data using multiple cost functions
David J. Abers, George Hripcsak, Lena Mamykina +2
This article develops a novel data assimilation methodology, addressing challenges that are common in real-world settings, such as severe sparsity of observations, lack of reliable…
Do People Engage Cognitively with AI? Impact of AI Assistance on Incidental Learning
Krzysztof Z. Gajos, Lena Mamykina
When people receive advice while making difficult decisions, they often make better decisions in the moment and also increase their knowledge in the process. However, such incident…
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…
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…
Behavioral-clinical phenotyping with type 2 diabetes self-monitoring data
Matthew E. Levine, David J. Albers, Marissa Burgermaster +3
Objective: To evaluate unsupervised clustering methods for identifying individual-level behavioral-clinical phenotypes that relate personal biomarkers and behavioral traits in type…
Offline and online data assimilation for real-time blood glucose forecasting in type 2 diabetes
Matthew E Levine, George Hripcsak, Lena Mamykina +2
We evaluate the benefits of combining different offline and online data assimilation methodologies to improve personalized blood glucose prediction with type 2 diabetes self-monito…