Author: Burgermaster Lab

Read the full paper in the Oxford Academic! |Abstract| Objective: To develop and test a visual analytics tool to help clinicians identify systematic and clinically meaningful patterns in patient-generated data (PGD) while decreasing perceived information overload. Methods: Participatory design was used to develop Glucolyzer, an interactive tool featuring hierarchical clustering and a heatmap visualization to…

Full paper available on SAGE Journals |Abstract| The purpose of this study was to determine the level of integration of school gardens and identify factors that predict integration. 211 New York City schools completed a survey that collected demographic information and utilized the School Garden Integration Scale. A mean garden integration score was calculated, and…

Keep reading in Cornell University Journal! |Abstract| Objective: To evaluate unsupervised clustering methods for identifying individual-level behavioral-clinical phenotypes that relate personal biomarkers and behavioral traits in type 2 diabetes (T2DM) self-monitoring data. Materials and Methods: We used hierarchical clustering (HC) to identify groups of meals with similar nutrition and glycemic impact for 6 individuals with…