Michele Bevilacqua
- Artificial Intelligence top 10%
- Molecular Biology
- Surgery
- Epidemiology
- Cardiology and Cardiovascular Medicine
- Co-authors
- John HewittFabio PetroniAshwin ParanjapeNelson F. LiuKevin LinPercy LiangAndrea DalbeniFilippo Cattazzo
- Topics
- Liver Disease Diagnosis and Treatment (9 papers)Liver Disease and Transplantation (5 papers)Cardiovascular Disease and Adiposity (3 papers)
- Partner nations
- ItalyAustriaUnited Kingdom
In The Last Decade
Michele Bevilacqua
42 papers receiving 621 citations
Hit Papers
Peers
Comparison fields: 5 of 129
- Artificial Intelligence 187
- Molecular Biology 86
- Surgery 78
- Epidemiology 76
- Cardiology and Cardiovascular Medicine 67
Countries citing papers authored by Michele Bevilacqua
This map shows the geographic impact of Michele Bevilacqua'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 Michele Bevilacqua with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Michele Bevilacqua more than expected).
Fields of papers citing papers by Michele Bevilacqua
This network shows the impact of papers produced by Michele Bevilacqua. 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 Michele Bevilacqua. The network helps show where Michele Bevilacqua may publish in the future.
Co-authorship network of co-authors of Michele Bevilacqua
This figure shows the co-authorship network connecting the top 25 collaborators of Michele Bevilacqua. A scholar is included among the top collaborators of Michele Bevilacqua 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 Michele Bevilacqua. Michele Bevilacqua is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | Lost in the Middle: How Language Models Use Long Contextsbreakdown → | 285 |
| 3 | 1 | |
| 4 | 10 | |
| 5 | 6 | |
| 6 | 4 | |
| 7 | 2 | |
| 8 | 5 | |
| 9 | 4 | |
| 10 | 6 | |
| 11 | 4 | |
| 12 | 20 | |
| 13 | 17 | |
| 14 | 3 | |
| 15 | 0 | |
| 16 | 1 | |
| 17 | 16 | |
| 18 | Foschi D, Corsi F, Lazzorini M, et al. Treatment of morbid obesity by intraparietogastric administration of botulinum toxin: a randomized, double-blind, controlled study | 1 |
| 19 | 1 | |
| 20 | 11 |
About Michele Bevilacqua
Michele Bevilacqua is a scholar working on Hepatology, Behavioral Neuroscience and Cardiology and Cardiovascular Medicine, having authored 44 papers that have together received 648 indexed citations. Recurring topics across this work include Liver Disease Diagnosis and Treatment (9 papers), Liver Disease and Transplantation (5 papers) and Cardiovascular Disease and Adiposity (3 papers). The work is most often cited by research in Health Informatics (26 citations), Artificial Intelligence (187 citations) and Software (16 citations). Michele Bevilacqua has collaborated with scholars based in Italy, Austria and United Kingdom. Frequent co-authors include John Hewitt, Fabio Petroni, Ashwin Paranjape, Nelson F. Liu, Kevin Lin, Percy Liang, Andrea Dalbeni, Filippo Cattazzo, Cristiano Fava and Plinio Cirillo. Their work appears in journals such as PLoS ONE, Endocrinology and Critical Care Medicine.
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.