23 citations · 28 across the 6 of their papers we have counts for
6 papers
GlucoTune: A Unified Framework for Blood Glucose Preprocessing, Forecasting, and Benchmarking in Diabetes
Davide Marelli, Giorgia Rigamonti, Mirko Paolo Barbato +1
Preprocessing blood glucose time-series data is a critical yet often overlooked step in developing data-driven methods for diabetes management, particularly for type 1 diabetes. Th…
Subject-Conditioned Glucose Forecasting in Type-1 Diabetes
Giorgia Rigamonti, Mirko Paolo Barbato, Davide Marelli +1
Accurate forecasting of blood glucose concentration is key in the management of Type 1 Diabetes, facilitating early detection of adverse glycemic events and supporting timely thera…
Tailoring Adverse Event Prediction in Type 1 Diabetes with Patient-Specific Deep Learning Models
Giorgia Rigamonti, Mirko Paolo Barbato, Davide Marelli +1
Effective management of Type 1 Diabetes requires continuous glucose monitoring and precise insulin adjustments to prevent hyperglycemia and hypoglycemia. With the growing adoption…
Lightweight Sequential Transformers for Blood Glucose Level Prediction in Type-1 Diabetes
Mirko Paolo Barbato, Giorgia Rigamonti, Davide Marelli +1
Type 1 Diabetes (T1D) affects millions worldwide, requiring continuous monitoring to prevent severe hypo- and hyperglycemic events. While continuous glucose monitoring has improved…
Deep Learning Hyperspectral Pansharpening on large scale PRISMA dataset
Simone Zini, Mirko Paolo Barbato, Flavio Piccoli +1
In this work, we assess several deep learning strategies for hyperspectral pansharpening. First, we present a new dataset with a greater extent than any other in the state of the a…
Unsupervised Segmentation of Hyperspectral Remote Sensing Images with Superpixels
Mirko Paolo Barbato, Paolo Napoletano, Flavio Piccoli +1
In this paper, we propose an unsupervised method for hyperspectral remote sensing image segmentation. The method exploits the mean-shift clustering algorithm that takes as input a…