Jakob De Geer

16 papers receiving 533 citations

Hit Papers

Diagnostic Accuracy of a Machine-Learning Approach to Cor...2018202620202023201850100150200250

Peers

Jakob De Geer
Comparison fields: 5 of 36
  • Radiology, Nuclear Medicine and Imaging 494
  • Surgery 249
  • Biomedical Engineering 231
  • Cardiology and Cardiovascular Medicine 186
  • Pulmonary and Respiratory Medicine 52
Replace Kranthi K. Kolli with:
Kranthi K. Kolli United States
Maximilian J. Bauer United States
Gilberto J. Aquino United States
Puneet Sharma United States
Mark Lemley United States
Kazuhisa Takamura Japan
Sabrina Oebel Germany
Meng Jie Lu China
Georgios Rampidis Greece
Marion Carrier France
Jakob De Geer relative to Kranthi K. Kolli United States Kranthi K. Kolli's profile →
Citations per field
00.5×2.6×
Kranthi K. Kolli · 1×
Citations per year

Countries citing papers authored by Jakob De Geer

Since Specialization
Citations

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

Fields of papers citing papers by Jakob De Geer

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jakob De Geer. 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 Jakob De Geer. The network helps show where Jakob De Geer may publish in the future.

Co-authorship network of co-authors of Jakob De Geer

This figure shows the co-authorship network connecting the top 25 collaborators of Jakob De Geer. A scholar is included among the top collaborators of Jakob De Geer 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 Jakob De Geer. Jakob De Geer is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

17 of 17 papers shown
#WorkIndexed citations
1 5
2 53
3 75
4 6
5 14
6 3
7
Diagnostic Accuracy of a Machine-Learning Approach to Coronary Computed Tomographic Angiography–Based Fractional Flow Reservebreakdown →
271
8 42
9 3
10 21
11 12
12 9
13 3
14 0
15 9
16 11
17 2

About Jakob De Geer

Jakob De Geer is a scholar working on Radiology, Nuclear Medicine and Imaging, Biomedical Engineering and Surgery, having authored 17 papers that have together received 539 indexed citations. Recurring topics across this work include Cardiac Imaging and Diagnostics (11 papers), Advanced X-ray and CT Imaging (9 papers) and Coronary Interventions and Diagnostics (6 papers). The work is most often cited by research in Health Informatics (34 citations), Radiology, Nuclear Medicine and Imaging (494 citations) and Cardiology and Cardiovascular Medicine (186 citations). Jakob De Geer has collaborated with scholars based in Sweden, United States and Netherlands. Frequent co-authors include Anders Persson, U. Joseph Schoepf, Cezary Kępka, Koen Nieman, Dong Hyun Yang, Adriaan Coenen, Christian Tesche, Young‐Hak Kim, Mariusz Kruk and Puneet Sharma. Their work appears in journals such as The American Journal of Cardiology, American Journal of Roentgenology and Journal of Molecular and Cellular 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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