Giada Acciaroli
Impact in
-
- Diabetes Management and Research
-
- Artificial Intelligence in Healthcare
Papers in ⓘ
-
- Diabetes Management and Research 14
- Surgery 8
- Pancreatic function and diabetes 7
- Co-authors
- Andrea Facchinetti (12 shared papers)Giovanni Sparacino (12 shared papers)Martina Vettoretti (8 shared papers)Giacomo Cappon (2 shared papers)Claudio Cobelli (3 shared papers)John Welsh (1 shared paper)Halis Kaan Aktürk (1 shared paper)Enrico Longato (2 shared papers)
- Journals
- Journal of Diabetes Science and Technology (4 papers)Diabetes Technology & Therapeutics (2 papers)Diabetic Medicine (2 papers)Computers in Biology and Medicine (1 paper)IEEE Transactions on Biomedical Engineering (1 paper)
- Partner nations
- ItalyFinlandUnited States
In The Last Decade
Giada Acciaroli
16 papers receiving 476 citations
Peers
Comparison fields: 5 of 81
- Endocrinology, Diabetes and Metabolism 249
- Health Information Management 41
- Biophysics 45
- Bioengineering 44
- Genetics 121
Countries citing papers authored by Giada Acciaroli
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
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-authors
The 23 scholars most cited alongside Giada Acciaroli, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2017 | 179 | |
| 2 | 2018 | 78 | |
| 3 | 2018 | 66 | |
| 4 | 2017 | 33 | |
| 5 | 2017 | 24 | |
| 6 | 2021 | 19 | |
| 7 | 2016 | 17 | |
| 8 | 2018 | 16 | |
| 9 | 2017 | 15 | |
| 10 | 2019 | 13 | |
| 11 | 2019 | 12 | |
| 12 | 2018 | 11 | |
| 13 | 2023 | 6 | |
| 14 | 2022 | 4 | |
| 15 | 2018 | 2 | |
| 16 | 2018 | 1 |
About Giada Acciaroli
Giada Acciaroli is a scholar working on Endocrinology, Diabetes and Metabolism, Surgery, Genetics, Biomedical Engineering and Electrical and Electronic Engineering, having authored 16 papers that have together received 496 indexed citations. Recurring topics across this work include Diabetes Management and Research (14 papers), Pancreatic function and diabetes (7 papers), Diabetes and associated disorders (7 papers), Electrochemical sensors and biosensors (3 papers), Artificial Intelligence in Healthcare (2 papers), Spectroscopy Techniques in Biomedical and Chemical Research (2 papers), Non-Invasive Vital Sign Monitoring (2 papers) and Wireless Body Area Networks (2 papers). The work is most often cited by research in Endocrinology, Diabetes and Metabolism (249 citations), Health Information Management (41 citations), Biophysics (45 citations), Bioengineering (44 citations) and Genetics (121 citations). Giada Acciaroli has collaborated with scholars based in Italy, Finland and United States. Frequent co-authors include Andrea Facchinetti, Giovanni Sparacino, Martina Vettoretti, Giacomo Cappon, Claudio Cobelli, John Welsh, Halis Kaan Aktürk, Enrico Longato, Alberto Maran and Liisa Hakaste. Their work appears in journals such as Journal of Diabetes Science and Technology, Diabetes Technology & Therapeutics, Diabetic Medicine, Computers in Biology and Medicine and IEEE Transactions on Biomedical Engineering.
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.