Marta Baviera

2.5k citations
48 papers · 1.1k · h-index 21

Impact in

Papers in

Marta Baviera

41 papers receiving 1.1k citations

Peers

Marta Baviera
Comparison fields: 5 of 96
  • Cellular and Molecular Neuroscience 351
  • Geriatrics and Gerontology 46
  • Biological Psychiatry 33
  • Endocrinology, Diabetes and Metabolism 184
  • Family Practice 15
Replace Paul R. Gard with:
Paul R. Gard United Kingdom
Nancy C. Tkacs United States
Ramit Ravona‐Springer Israel
Subramoniam Madhusoodanan United States
Laurie Barclay United States
Jonathan G. Leung United States
Ann Robinson Canada
Ioannis Liappas Greece
Robert L. Dufresne United States
J. Caudle United States
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Citations per field
00.5×
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Citations per year

Countries citing papers authored by Marta Baviera

Since Specialization
Citations

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

Fields of papers citing papers by Marta Baviera

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Marta Baviera, 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 Marta Baviera Line = papers co-authored together Marta Baviera links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 48 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2005160
2 200493
3 200470
4 201167
5 201157
6 200450
7 201046
8 200739
9 201137
10 202234
11 200833
12 202130
13 200128
14 201627
15 202225
16 201524
17 201424
18 201622
19 201521
20 201521

About Marta Baviera

Marta Baviera is a scholar working on Endocrinology, Diabetes and Metabolism, Cellular and Molecular Neuroscience, Cardiology and Cardiovascular Medicine, Cognitive Neuroscience and Pulmonary and Respiratory Medicine, having authored 48 papers that have together received 1.1k indexed citations. Recurring topics across this work include Diabetes Treatment and Management (7 papers), Neurotransmitter Receptor Influence on Behavior (6 papers), Neuroscience and Neuropharmacology Research (5 papers), Atrial Fibrillation Management and Outcomes (4 papers), Memory and Neural Mechanisms (4 papers), Pharmaceutical Practices and Patient Outcomes (3 papers), Venous Thromboembolism Diagnosis and Management (2 papers) and Systemic Lupus Erythematosus Research (2 papers). The work is most often cited by research in Cellular and Molecular Neuroscience (351 citations), Geriatrics and Gerontology (46 citations), Biological Psychiatry (33 citations), Endocrinology, Diabetes and Metabolism (184 citations) and Family Practice (15 citations). Marta Baviera has collaborated with scholars based in Italy, United States and Iceland. Frequent co-authors include Mirjana Carli, Roberto William Invernizzi, Claudia Balducci, Maria Carla Roncaglioni, Ida Fortino, Mauro Tettamanti, Luca Merlino, Angela Bortolotti, Alessandro Nobili and Eleonora Calcagno. Their work appears in journals such as Diabetes Research and Clinical Practice, Cardiovascular Diabetology, Acta Diabetologica, Diabetic Medicine and International Journal of Cardiology.

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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