Background Precision medicine, targeting treatments to individual genetic and clinical
profiles, faces challenges in data collection, costs, and privacy. Generative AI offers a …

Health-related technologies are starting to make use of context awareness, a pervasive
computing field that has begun to impact healthcare infrastructure. People and healthcare …

Abstract Background Type 1 diabetes (T1D) simulators, crucial for advancing diabetes
treatments, often fall short of capturing the entire complexity of the glucose-insulin system …

The automated analysis of medical time series, such as the electrocardiogram (ECG),
electroencephalogram (EEG), pulse oximetry, etc, has the potential to serve as a valuable …

An increasing amount of research is incorporating the concept of Digital twin (DT) in
biomedical and health care applications. This scoping review aims to summarize existing …

Artificial pancreas requires data from multiple sources for accurate insulin dose estimation.
These include data from continuous glucose sensors, past insulin dosage information, meal …

This paper proposes a 1.75-nW continuous tear-glucose monitoring/data-storing IC using
5.5-GHz wireless backscatter data-readout for self-powered Smart Contact Lenses (SCL). It …

The escalating prevalence of Type 2 Diabetes (T2D) represents a substantial burden on
global healthcare systems, especially in regions such as Mexico. Existing diagnostic …

The incidence of diabetes has been increasing, resulting in an increasing cost of managing
and tracking the correlates for blood glucose levels. Just for New Zealand alone, 2.1 billion …

Generative Adversarial Networks (GANs) have emerged as tools for creating synthetic data
that mimics real datasets. Time series GANs extend GANs concept by attempting to replicate …