Daniel T. Grima

2.2k citations
62 papers · 1.8k · h-index 19

Impact in

Papers in

Daniel T. Grima

61 papers receiving 1.7k citations

Peers

Daniel T. Grima
Comparison fields: 5 of 113
  • Epidemiology 624
  • Orthopedics and Sports Medicine 141
  • Hematology 133
  • Applied Microbiology and Biotechnology 21
  • Pathology and Forensic Medicine 156
Replace Eoghan M. McCarthy with:
Eoghan M. McCarthy United Kingdom
Evelyn Hsieh United States
María José Pérez‐Sáez Spain
Faye Moore United Kingdom
Michael Wernecke United States
Paul Greaves United Kingdom
Jacqueline Neuhaus United States
Ben Parker United Kingdom
Nina Friis‐Møller Denmark
Giorgio Lorenzo Colombo Italy
Daniel T. Grima relative to Eoghan M. McCarthy United Kingdom Eoghan M. McCarthy's profile →
Citations per field
00.5×2×4×6.7×
Eoghan M. McCarthy · 1×
Citations per year

Countries citing papers authored by Daniel T. Grima

Since Specialization
Citations

This map shows the geographic impact of Daniel T. Grima'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 Daniel T. Grima with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Daniel T. Grima more than expected).

Fields of papers citing papers by Daniel T. Grima

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Daniel T. Grima. 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 Daniel T. Grima. The network helps show where Daniel T. Grima may publish in the future.

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 62 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2004446
2 2003182
3 2014181
4 2000128
5 2004124
6 201296
7 200189
8 201241
9 200740
10 199830
11 201328
12 201026
13 200325
14 201024
15 202124
16 202022
17 201819
18 201219
19 200719
20 200617

About Daniel T. Grima

Daniel T. Grima is a scholar working on Economics and Econometrics, Orthopedics and Sports Medicine, Nephrology, Hematology and Cardiology and Cardiovascular Medicine, having authored 62 papers that have together received 1.8k indexed citations. Recurring topics across this work include Health Systems, Economic Evaluations, Quality of Life (12 papers), Economic and Financial Impacts of Cancer (6 papers), Multiple Myeloma Research and Treatments (6 papers), Pharmaceutical Economics and Policy (5 papers), Bone health and osteoporosis research (5 papers), Amyloidosis: Diagnosis, Treatment, Outcomes (3 papers), Multiple Sclerosis Research Studies (3 papers) and Parathyroid Disorders and Treatments (3 papers). The work is most often cited by research in Epidemiology (624 citations), Orthopedics and Sports Medicine (141 citations), Hematology (133 citations), Applied Microbiology and Biotechnology (21 citations) and Pathology and Forensic Medicine (156 citations). Daniel T. Grima has collaborated with scholars based in Canada, United States and United Kingdom. Frequent co-authors include Milton C. Weinstein, Michele A. Kohli, Thomas C. Wright, Eduardo Luis Franco, Francesc Xavier Bosch, Sheila Jesolit C. S. Goldie, Sue J. Goldie, Jonathan Derrick Adachi, Lisa M. Bernard and Brian F. Hutton. Their work appears in journals such as Value in Health, PharmacoEconomics, Blood, Osteoporosis International and Journal of Medical Economics.

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.

Explore authors with similar magnitude of impact