Marc C. Huisman

4.8k citations
114 papers · 2.9k indexed · h-index 33
Topics
Medical Imaging Techniques and Applications (48 papers)Radiopharmaceutical Chemistry and Applications (41 papers)Radiomics and Machine Learning in Medical Imaging (23 papers)

In The Last Decade

Marc C. Huisman

111 papers receiving 2.9k citations

Peers

Marc C. Huisman
Comparison fields: 5 of 112
  • Radiology, Nuclear Medicine and Imaging 1.9k
  • Oncology 753
  • Pulmonary and Respiratory Medicine 438
  • Molecular Biology 403
  • Cardiology and Cardiovascular Medicine 335
Replace Seigo Kinuya with:
Seigo Kinuya Japan
Anne Roivainen Finland
Sean Smart United Kingdom
Tobias L. Roß Germany
Carla F.M. Molthoff Netherlands
Samuel Samnick Germany
Makoto Hosono Japan
Johan R. de Jong Netherlands
Rudolf A. Werner Germany
Luc Mortelmans Belgium
Marc C. Huisman relative to Seigo Kinuya Japan Seigo Kinuya's profile →
Citations per field
00.5×1.5×
Seigo Kinuya · 1×
Citations per year

Countries citing papers authored by Marc C. Huisman

Since Specialization
Citations

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

Fields of papers citing papers by Marc C. Huisman

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Marc C. Huisman. 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 Marc C. Huisman. The network helps show where Marc C. Huisman may publish in the future.

Co-authorship network of co-authors of Marc C. Huisman

This figure shows the co-authorship network connecting the top 25 collaborators of Marc C. Huisman. A scholar is included among the top collaborators of Marc C. Huisman based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Marc C. Huisman. Marc C. Huisman is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
#WorkIndexed citations
1 0
2 3
3 0
4 19
5 18
6 11
7 104
8 16
9
Immuno-positron emission tomography with zirconium-89-labeled monoclonal antibodies in oncology
3
10 1
11 6
12 3
13 3
14 5
15 44
16 12
17 14
18 42
19 133
20 127

About Marc C. Huisman

Marc C. Huisman is a scholar working on Radiology, Nuclear Medicine and Imaging, Oncology and Radiation, having authored 114 papers that have together received 2.9k indexed citations. Recurring topics across this work include Medical Imaging Techniques and Applications (48 papers), Radiopharmaceutical Chemistry and Applications (41 papers) and Radiomics and Machine Learning in Medical Imaging (23 papers). The work is most often cited by research in Radiology, Nuclear Medicine and Imaging (1.9k citations), Oncology (753 citations) and Immunology and Allergy (101 citations). Marc C. Huisman has collaborated with scholars based in Netherlands, United States and Germany. Frequent co-authors include Adriaan A. Lammertsma, Daniëlle J. Vugts, Ronald Boellaard, Otto S. Hoekstra, Guus A.M.S. van Dongen, C. Willemien Menke‐van der Houven van Oordt, Albert D. Windhorst, Markus Schwaiger, Sybille Reder and Carla F.M. Molthoff. Their work appears in journals such as Advanced Materials, Journal of Clinical Oncology and Journal of the American College 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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