Giada Acciaroli

737 total citations
16 papers, 496 citations indexed

About

Giada Acciaroli is a scholar working on Endocrinology, Diabetes and Metabolism, Surgery and Genetics. According to data from OpenAlex, Giada Acciaroli has authored 16 papers receiving a total of 496 indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Endocrinology, Diabetes and Metabolism, 8 papers in Surgery and 7 papers in Genetics. Recurrent topics in Giada Acciaroli's work include Diabetes Management and Research (14 papers), Diabetes and associated disorders (7 papers) and Pancreatic function and diabetes (7 papers). Giada Acciaroli is often cited by papers focused on Diabetes Management and Research (14 papers), Diabetes and associated disorders (7 papers) and Pancreatic function and diabetes (7 papers). Giada Acciaroli collaborates with scholars based in Italy, Finland and United States. Giada Acciaroli's co-authors include Giovanni Sparacino, Andrea Facchinetti, Martina Vettoretti, Giacomo Cappon, Claudio Cobelli, Halis Kaan Aktürk, John Welsh, Alberto Maran, Enrico Longato and Liisa Hakaste and has published in prestigious journals such as IEEE Transactions on Biomedical Engineering, Sensors and Diabetic Medicine.

In The Last Decade

Giada Acciaroli

16 papers receiving 476 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Giada Acciaroli Italy 12 249 156 148 121 111 16 496
Michael Schoemaker Germany 13 447 1.8× 140 0.9× 300 2.0× 190 1.6× 95 0.9× 16 643
Geoffrey McGarraugh United States 8 311 1.2× 117 0.8× 207 1.4× 126 1.0× 94 0.8× 9 451
Manuela Link Germany 18 827 3.3× 160 1.0× 410 2.8× 312 2.6× 93 0.8× 37 1.0k
D. Barry Keenan United States 11 374 1.5× 99 0.6× 288 1.9× 201 1.7× 55 0.5× 17 621
David Ahn United States 9 218 0.9× 47 0.3× 98 0.7× 90 0.7× 44 0.4× 21 386
F. Bischof Germany 9 188 0.8× 91 0.6× 113 0.8× 50 0.4× 140 1.3× 13 375
C. Meyerhoff Germany 11 194 0.8× 110 0.7× 116 0.8× 52 0.4× 166 1.5× 15 412
Narvada Jugnee United Kingdom 9 364 1.5× 64 0.4× 273 1.8× 248 2.0× 27 0.2× 13 489
Zeinab Mahmoudi Denmark 12 189 0.8× 43 0.3× 102 0.7× 88 0.7× 21 0.2× 24 305
Eleonora M. Aiello United States 10 197 0.8× 32 0.2× 120 0.8× 98 0.8× 36 0.3× 22 278

Countries citing papers authored by Giada Acciaroli

Since Specialization
Citations

This map shows the geographic impact of Giada Acciaroli's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Giada Acciaroli with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Giada Acciaroli more than expected).

Fields of papers citing papers by Giada Acciaroli

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Giada Acciaroli. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Giada Acciaroli. The network helps show where Giada Acciaroli may publish in the future.

Co-authorship network of co-authors of Giada Acciaroli

This figure shows the co-authorship network connecting the top 25 collaborators of Giada Acciaroli. A scholar is included among the top collaborators of Giada Acciaroli based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Giada Acciaroli. Giada Acciaroli is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

16 of 16 papers shown
1.
Acciaroli, Giada, et al.. (2023). G6 continuous glucose monitoring system feature use and its associations with glycaemia in Europe. Diabetic Medicine. 40(6). e15093–e15093. 6 indexed citations
2.
Acciaroli, Giada, et al.. (2022). Longitudinal analysis of users transitioning from the Dexcom G5 to the G6 RT‐CGM system in Germany, Sweden and the United Kingdom (2018–2020). Diabetic Medicine. 40(2). e14946–e14946. 4 indexed citations
3.
Acciaroli, Giada, John Welsh, & Halis Kaan Aktürk. (2021). Mitigation of Rebound Hyperglycemia With Real-Time Continuous Glucose Monitoring Data and Predictive Alerts. Journal of Diabetes Science and Technology. 16(3). 677–682. 19 indexed citations
4.
Longato, Enrico, Giada Acciaroli, Andrea Facchinetti, Alberto Maran, & Giovanni Sparacino. (2019). Simple Linear Support Vector Machine Classifier Can Distinguish Impaired Glucose Tolerance Versus Type 2 Diabetes Using a Reduced Set of CGM-Based Glycemic Variability Indices. Journal of Diabetes Science and Technology. 14(2). 297–302. 13 indexed citations
5.
Acciaroli, Giada, et al.. (2019). Retrospective Continuous-Time Blood Glucose Estimation in Free Living Conditions with a Non-Invasive Multisensor Device. Sensors. 19(17). 3677–3677. 12 indexed citations
6.
Longato, Enrico, Giada Acciaroli, Andrea Facchinetti, et al.. (2018). Glycaemic variability-based classification of impaired glucose tolerance vs. type 2 diabetes using continuous glucose monitoring data. Computers in Biology and Medicine. 96. 141–146. 16 indexed citations
7.
Acciaroli, Giada, Andrea Facchinetti, Gianluigi Pillonetto, & Giovanni Sparacino. (2018). Non-Invasive Continuous-Time Blood Pressure Estimation from a Single Channel PPG Signal using Regularized ARX Models. PubMed. 2018. 3630–3633. 11 indexed citations
8.
Acciaroli, Giada, Martina Vettoretti, Andrea Facchinetti, & Giovanni Sparacino. (2018). Calibration of Minimally Invasive Continuous Glucose Monitoring Sensors: State-of-The-Art and Current Perspectives. Biosensors. 8(1). 24–24. 78 indexed citations
9.
Schiavon, Michele, et al.. (2018). A Model of Acetaminophen Pharmacokinetics and its Effect on Continuous Glucose Monitoring Sensor Measurements. PubMed. 38. 159–162. 2 indexed citations
10.
Vettoretti, Martina, Giacomo Cappon, Giada Acciaroli, Andrea Facchinetti, & Giovanni Sparacino. (2018). Continuous Glucose Monitoring: Current Use in Diabetes Management and Possible Future Applications. Journal of Diabetes Science and Technology. 12(5). 1064–1071. 66 indexed citations
11.
Acciaroli, Giada, Martina Vettoretti, Andrea Facchinetti, & Giovanni Sparacino. (2018). Bayesian Model Selection Framework to Improve Calibration of Continuous Glucose Monitoring Sensors for Diabetes Management. PubMed. 1. 29–32. 1 indexed citations
12.
Acciaroli, Giada, Martina Vettoretti, Andrea Facchinetti, & Giovanni Sparacino. (2017). Toward Calibration-Free Continuous Glucose Monitoring Sensors: Bayesian Calibration Approach Applied to Next-Generation Dexcom Technology. Diabetes Technology & Therapeutics. 20(1). 59–67. 15 indexed citations
13.
Acciaroli, Giada, Martina Vettoretti, Andrea Facchinetti, Giovanni Sparacino, & Claudio Cobelli. (2017). Reduction of Blood Glucose Measurements to Calibrate Subcutaneous Glucose Sensors: A Bayesian Multiday Framework. IEEE Transactions on Biomedical Engineering. 65(3). 587–595. 24 indexed citations
14.
Cappon, Giacomo, Giada Acciaroli, Martina Vettoretti, Andrea Facchinetti, & Giovanni Sparacino. (2017). Wearable Continuous Glucose Monitoring Sensors: A Revolution in Diabetes Treatment. Electronics. 6(3). 65–65. 179 indexed citations
15.
Acciaroli, Giada, Giovanni Sparacino, Liisa Hakaste, et al.. (2017). Diabetes and Prediabetes Classification Using Glycemic Variability Indices From Continuous Glucose Monitoring Data. Journal of Diabetes Science and Technology. 12(1). 105–113. 33 indexed citations
16.
Acciaroli, Giada, Martina Vettoretti, Andrea Facchinetti, Giovanni Sparacino, & Claudio Cobelli. (2016). From Two to One Per Day Calibration of Dexcom G4 Platinum by a Time-Varying Day-Specific Bayesian Prior. Diabetes Technology & Therapeutics. 18(8). 472–479. 17 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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