30 citations · 40 across the 6 of their papers we have counts for
8 papers
Evaluating Type-1 Diabetes Digital Twins by Decision Quality
Victor Li, Owen Tucker, Michael S. Hughes +2
A digital twin (DT) for type 1 diabetes (T1D) can predict how an individual's blood glucose will respond to different insulin treatments without actually trying them. For each trea…
GlucoFM-Bench: Benchmarking Time-Series Foundation Models for Blood Glucose Forecasting
Baiying Lu, Zhaohui Liang, Ryan Pontius +2
Blood glucose forecasting models are foundational for modern diabetes management systems, as reliable short-term predictions can enable proactive interventions, support automated i…
If Only My CGM Could Speak: A Privacy-Preserving Agent for Question Answering over Continuous Glucose Data
Yanjun Cui, Ali Emami, Temiloluwa Prioleau +1
Continuous glucose monitors (CGMs) used in diabetes care collect rich personal health data that could improve day-to-day self-management. However, current patient platforms only of…
Glucose-ML: A collection of longitudinal diabetes datasets for development of robust AI solutions
Temiloluwa Prioleau, Baiying Lu, Yanjun Cui
Artificial intelligence (AI) algorithms are a critical part of state-of-the-art digital health technology for diabetes management. Yet, access to large high-quality datasets is cre…
DiaTrend: A dataset from advanced diabetes technology to enable development of novel analytic solutions
Temiloluwa Prioleau, Abigail Bartolome, Richard Comi +1
Objective digital data is scarce yet needed in many domains to enable research that can transform the standard of healthcare. While data from consumer-grade wearables and smartphon…
Feature Selection for Multivariate Time Series via Network Pruning
Kang Gu, Soroush Vosoughi, Temiloluwa Prioleau
In recent years, there has been an ever increasing amount of multivariate time series (MTS) data in various domains, typically generated by a large family of sensors such as wearab…
Understanding Reflection Needs for Personal Health Data in Diabetes
Temiloluwa Prioleau, Ashutosh Sabharwal, Madhuri M. Vasudevan
To empower users of wearable medical devices, it is important to enable methods that facilitate reflection on previous care to improve future outcomes. In this work, we conducted a…
Adherence to Personal Health Devices: A Case Study in Diabetes Management
Sudip Vhaduri, Temiloluwa Prioleau
Personal health devices can enable continuous monitoring of health parameters. However, the benefit of these devices is often directly related to the frequency of use. Therefore, a…