A crucial module of the widely applied machine learning (ML) model is the model training
phase, which involves large-scale training data, often including sensitive private data. ML …

Seasonal variations in glycemic trends remain largely unstudied despite the growing
prevalence of diabetes. To address this gap, our objective is to investigate temporal …

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 …

Digital biomarkers can radically transform the standard of care for chronic conditions that are
complex to manage. In this work, we propose a scalable computational framework for …

Many patients with diabetes struggle with post-meal high blood glucose due to missed or
untimely meal-related insulin doses. To address this challenge, our research aims to:(1) …

The growing popularity of wearable devices for continuous sensing has made personal
health data increasingly available, yet methods for data interpretation are still a work in …

Maintaining good glycemic control is a central part of diabetes care. However, it can be a
tedious task because many factors in daily living can affect glycemic control. To support …

Continuous glucose monitors (CGM) and insulin pumps are becoming increasingly
important in diabetes management. Additionally, data streams from these devices enable …

Type 1 diabetes (T1D) is a complex autoimmune disease that currently cannot be cured,
only managed. Optimal treatment the of T1D symptoms, requires a multidisciplinary care …

Diabetes affects nearly 11.5% of the Indian population, and globally almost 18% of the total
population. High glucose levels cause the early signs of diabetes, if not treated, will lead to …