Daniela Pacella

70 papers receiving 645 citations

Peers

Daniela Pacella
Comparison fields: 5 of 117
  • Critical Care and Intensive Care Medicine 52
  • Applied Microbiology and Biotechnology 17
  • Endocrinology, Diabetes and Metabolism 105
  • Cardiology and Cardiovascular Medicine 99
  • Surgery 188
Replace David Ross with:
David Ross Canada
Anna Wallace United States
Amanda López Picado Spain
Siew‐Pang Chan Singapore
Wonhee Kim South Korea
Susan Wojcik United States
David Johnson United States
Karen E. Lynch United States
Hooman Bakhshandeh Iran
Pasquale Buonanno Italy
Daniela Pacella relative to David Ross Canada David Ross's profile →
Citations per field
00.5×9.2×
David Ross · 1×
Citations per year

Countries citing papers authored by Daniela Pacella

Since Specialization
Citations

This map shows the geographic impact of Daniela Pacella'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 Daniela Pacella with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Daniela Pacella more than expected).

Fields of papers citing papers by Daniela Pacella

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Daniela Pacella. 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 Daniela Pacella. The network helps show where Daniela Pacella may publish in the future.

Co-authors

The 25 scholars most cited alongside Daniela Pacella, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Daniela Pacella Line = papers co-authored together Daniela Pacella links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 81 papers — load more, or switch the sort, to bring in the rest.

#Work
1 202275
2 202335
3 202333
4 202130
5 201830
6 202225
7 202224
8 202423
9 202323
10 201922
11 202022
12 202120
13 202118
14 201718
15 202216
16 202216
17 202216
18 202414
19 202314
20 202312

About Daniela Pacella

Daniela Pacella is a scholar working on Cardiology and Cardiovascular Medicine, Endocrinology, Diabetes and Metabolism, Radiological and Ultrasound Technology, Critical Care and Intensive Care Medicine and Oncology, having authored 81 papers that have together received 662 indexed citations. Recurring topics across this work include Blood Pressure and Hypertension Studies (8 papers), Cardiovascular Function and Risk Factors (5 papers), Colorectal Cancer Surgical Treatments (5 papers), COVID-19 Clinical Research Studies (5 papers), Lipoproteins and Cardiovascular Health (5 papers), Diabetes Management and Research (4 papers), Cardiovascular Health and Disease Prevention (4 papers) and Health Systems, Economic Evaluations, Quality of Life (4 papers). The work is most often cited by research in Critical Care and Intensive Care Medicine (52 citations), Applied Microbiology and Biotechnology (17 citations), Endocrinology, Diabetes and Metabolism (105 citations), Cardiology and Cardiovascular Medicine (99 citations) and Surgery (188 citations). Daniela Pacella has collaborated with scholars based in Italy, United States and United Kingdom. Frequent co-authors include Belén López‐Pérez, Bruno Trimarco, Valentina Trimarco, Gaetano Santulli, Raffaele Izzo, Maria Virginia Manzi, Carmine Morisco, Maria Lembo, Pasquale Mone and Letizia Capasso. Their work appears in journals such as Journal of Clinical Medicine, Diabetes Research and Clinical Practice, Cancers, Nutrients and Safety and Health at Work.

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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