Jacob J. Visser

1.7k citations
56 papers · 786 indexed · h-index 15
Topics
Radiomics and Machine Learning in Medical Imaging (18 papers)Artificial Intelligence in Healthcare and Education (16 papers)Radiology practices and education (13 papers)

In The Last Decade

Jacob J. Visser

52 papers receiving 764 citations

Peers

Jacob J. Visser
Comparison fields: 5 of 85
  • Pulmonary and Respiratory Medicine 331
  • Radiology, Nuclear Medicine and Imaging 319
  • Cardiology and Cardiovascular Medicine 241
  • Health Informatics 134
  • Surgery 120
Replace Elizabeth Le with:
Elizabeth Le United Kingdom
Alla Iansavichene Canada
Arnaldo Dimagli United States
Quirina C. B. S. Thio United States
Olivier Q. Groot United States
David P. Stonko United States
Peter M. Graffy United States
Michiel E. R. Bongers United States
Andrew Lin United States
Diego Medvedofsky United States
Jacob J. Visser relative to Elizabeth Le United Kingdom Elizabeth Le's profile →
Citations per field
00.5×
Elizabeth Le · 1×
Citations per year

Countries citing papers authored by Jacob J. Visser

Since Specialization
Citations

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

Fields of papers citing papers by Jacob J. Visser

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jacob J. Visser. 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 Jacob J. Visser. The network helps show where Jacob J. Visser may publish in the future.

Co-authorship network of co-authors of Jacob J. Visser

This figure shows the co-authorship network connecting the top 25 collaborators of Jacob J. Visser. A scholar is included among the top collaborators of Jacob J. Visser 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 Jacob J. Visser. Jacob J. Visser 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 1
2 2
3 4
4 0
5 7
6 11
7 47
8 6
9 10
10 5
11 4
12 14
13 38
14 13
15 42
16 52
17 52
18 59
19 52
20
Anti-Mullerian hormone (AMH) protein expression in normal and polycystic human ovaries
1

About Jacob J. Visser

Jacob J. Visser is a scholar working on Health Informatics, Radiology, Nuclear Medicine and Imaging and Family Practice, having authored 56 papers that have together received 786 indexed citations. Recurring topics across this work include Radiomics and Machine Learning in Medical Imaging (18 papers), Artificial Intelligence in Healthcare and Education (16 papers) and Radiology practices and education (13 papers). The work is most often cited by research in Health Informatics (134 citations), Radiology, Nuclear Medicine and Imaging (319 citations) and Cardiology and Cardiovascular Medicine (241 citations). Jacob J. Visser has collaborated with scholars based in Netherlands, United States and Italy. Frequent co-authors include Johanna L. Bosch, M. G. Myriam Hunink, Marc R.H.M. van Sambeek, Bart S. Ferket, Ewout W. Steyerberg, J.K. Kievit, Sandra Spronk, Ersen B Colkesen, Martijn P. A. Starmans and Taye H. Hamza. Their work appears in journals such as Journal of the American College of Cardiology, PLoS ONE and Radiology.

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

Rankless by CCL
2026