Massimo Brunetti

742 citations
18 papers · 464 · h-index 10

Impact in

Papers in

Massimo Brunetti

16 papers receiving 440 citations

Peers

Massimo Brunetti
Comparison fields: 5 of 104
  • Economics and Econometrics 169
  • Ecological Modeling 26
  • Statistics, Probability and Uncertainty 40
  • Medical Terminology 1
  • Endocrinology, Diabetes and Metabolism 62
Replace Nathan S. McClure with:
Nathan S. McClure Canada
Reuel A. Stallones United States
Adam Streeter United Kingdom
Frank W. Beltman Netherlands
Bain United Kingdom
Dana Hawwash Belgium
Pascual Solanas Spain
Yi‐Sheng Chao Canada
Joyce P. Samuel United States
Jessie Nallely Zurita‐Cruz Mexico
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Citations per field
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Citations per year

Countries citing papers authored by Massimo Brunetti

Since Specialization
Citations

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

Fields of papers citing papers by Massimo Brunetti

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

18 of 18 papers shown
#Work
1 2012181
2 200171
3 199946
4 200141
5 201730
6 200124
7 201920
8 201915
9 199711
10 20119
11 20236
12 20073
13 20122
14 20032
15 20172
16 20031
17
Domande e risorse lavorative per la promozione del benessere lavorativo: una ricerca-intervento nell’Azienda Usl di Modena
20140
18 20170

About Massimo Brunetti

Massimo Brunetti is a scholar working on Economics and Econometrics, General Health Professions, Cardiology and Cardiovascular Medicine, Endocrinology, Diabetes and Metabolism and Surgery, having authored 18 papers that have together received 464 indexed citations. Recurring topics across this work include Health Systems, Economic Evaluations, Quality of Life (8 papers), Healthcare cost, quality, practices (4 papers), Disaster Response and Management (2 papers), Species Distribution and Climate Change (2 papers), Plant and animal studies (2 papers), Blood Pressure and Hypertension Studies (2 papers), Meta-analysis and systematic reviews (2 papers) and Chronic Disease Management Strategies (2 papers). The work is most often cited by research in Economics and Econometrics (169 citations), Ecological Modeling (26 citations), Statistics, Probability and Uncertainty (40 citations), Medical Terminology (1 citation) and Endocrinology, Diabetes and Metabolism (62 citations). Massimo Brunetti has collaborated with scholars based in Italy, United Kingdom and Canada. Frequent co-authors include Giovanni Apolone, Silvio Garattini, Eva Pagano, Holger J. Schünemann, Livio Garattini, Marina Davoli, Andrew D Oxman, Laura Amato, Fabrizio Tediosi and Roman Jaeschke. Their work appears in journals such as PharmacoEconomics, BMC Health Services Research, The Journal of Cardiovascular Surgery, International Journal of Technology Assessment in Health Care and Clinical Chemistry and Laboratory Medicine (CCLM).

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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