Daniel Capurro

3.1k citations
79 papers · 1.7k indexed · 1 hit paper · h-index 22

Daniel Capurro

67 papers receiving 1.7k citations

Hit Papers

Process mining in healthcare: A literature review3482016202620192022100200300

Peers

Daniel Capurro
Comparison fields: 5 of 145
  • Health Informatics 68
  • Management Information Systems 438
  • Health Information Management 178
  • Management Science and Operations Research 194
  • Health 106
Replace Amar K. Das with:
Amar K. Das United States
Sooyoung Yoo South Korea
Hyeoneui Kim United States
Bernd Blobel Germany
Ricardo Cruz‐Correia Portugal
Syed Sibte Raza Abidi Canada
Abdul Roudsari United Kingdom
Eric W. Ford United States
Nancy M. Lorenzi United States
Spencer S. Jones United States
Daniel Capurro relative to Amar K. Das United States Amar K. Das's profile →
Citations per field
00.5×4.1×
Amar K. Das · 1×
Citations per year

Countries citing papers authored by Daniel Capurro

Since Specialization
Citations

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

Fields of papers citing papers by Daniel Capurro

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

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

All Works

20 of 20 papers shown
#Work
1 20251
2 20250
3 20240
4 20240
5 20241
6 20241
7 20238
8 202246
9 20227
10 202029
11 20202
12 202047
13 201813
14 201835
15
PALIA-ER: Bringing Question-Driven Process Mining Closer to the Emergency Room.
20175
16
Process mining in healthcare: A literature reviewbreakdown →
2016348
17
Statistical Section Segmentation in Free-Text Clinical Records
201230
18 200726
19 20077
20 200416

About Daniel Capurro

Daniel Capurro is a scholar working on Health Information Management, Health Informatics, Medical Laboratory Technology, Management Information Systems and General Health Professions, having authored 79 papers that have together received 1.7k indexed citations. Recurring topics across this work include Business Process Modeling and Analysis (13 papers), Machine Learning in Healthcare (11 papers), Electronic Health Records Systems (9 papers), Telemedicine and Telehealth Implementation (8 papers), Mobile Health and mHealth Applications (7 papers), Data Quality and Management (6 papers), Medical Coding and Health Information (6 papers) and Biomedical Text Mining and Ontologies (5 papers). The work is most often cited by research in Health Informatics (68 citations), Management Information Systems (438 citations), Health Information Management (178 citations), Management Science and Operations Research (194 citations) and Health (106 citations). Daniel Capurro has collaborated with scholars based in Australia, Chile and United States. Frequent co-authors include Marcos Sepúlveda, Eric Rojas, Jorge Muñoz-Gama, Anne M. Turner, Gabriel Rada, Jonathan Joe, Katrin Kirchhoff, Luz María Letelier S, Karin Verspoor and Anthony Nguyen. Their work appears in journals such as Journal of Biomedical Informatics, Journal of Medical Internet Research, International Journal of Environmental Research and Public Health, JMIR mhealth and uhealth and Journal of the American Medical Informatics Association.

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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