Predictive Glucose Modeling is a computational method that distinguishes itself by forecasting future glucose concentrations based on historical and real-time continuous glucose monitoring data using mathematical or machine learning algorithms.
434
Publications
21.4K
Citations
1.4K
Authors
579
Institutions
Publications per year
2017–2026
282
Publications
434
1–5 of 434
Authors
1.4K
- CC
17
h-index
- AF
16
h-index
- GS
14
h-index
- PG
13
h-index
- PH
12
h-index
1–5 of 1.4K
Institutions
579
University of Padua
Padua, Italy
22 h-index
103 publications
9.2K citations
Imperial College London
London, United Kingdom
13 h-index
59 publications
5.9K citations
University of Patras
Pátrai, Greece
10 h-index
20 publications
1.4K citations
University of Ioannina
Ioannina, Greece
10 h-index
25 publications
1.5K citations
Universitat Politècnica de València
Valencia, Spain
10 h-index
21 publications
530 citations
University of Pavia
Pavia, Italy
10 h-index
30 publications
2.8K citations
Illinois Institute of Technology
Chicago, United States
9 h-index
29 publications
1.2K citations
Universitat de Girona
Girona, Spain
8 h-index
19 publications
590 citations
1–8 of 579
Venues
- Diabetes Technology & Therapeutics
20 publications · 1.6K citations
19
h-index
- Journal of Diabetes Science and Technology
DST · 20 publications · 1.3K citations
18
h-index
- Computer Methods and Programs in Biomedicine
13 publications · 556 citations
13
h-index
- IEEE Transactions on Biomedical Engineering
13 publications · 1.2K citations
13
h-index
- Sensors
13 publications · 467 citations
12
h-index
1–5