Michael Puesken

602 citations
31 papers · 428 indexed · h-index 12
Topics
Radiomics and Machine Learning in Medical Imaging (11 papers)Medical Imaging Techniques and Applications (10 papers)Lung Cancer Diagnosis and Treatment (7 papers)

In The Last Decade

Michael Puesken

31 papers receiving 420 citations

Peers

Michael Puesken
Comparison fields: 5 of 59
  • Radiology, Nuclear Medicine and Imaging 225
  • Biomedical Engineering 150
  • Pulmonary and Respiratory Medicine 115
  • Surgery 73
  • Oncology 38
Replace Saravanabavaan Suntharalingam with:
Saravanabavaan Suntharalingam Germany
Vincent Schwarze Germany
Fabrizio Boni Italy
Cristina Marrocchio Italy
Ginevra Danti Italy
A. Bleuzen France
Gopal R. Vijayaraghavan United States
Zilai Pan China
Andrea Coppola Italy
Sung Kyoung Moon South Korea
Michael Puesken relative to Saravanabavaan Suntharalingam Germany Saravanabavaan Suntharalingam's profile →
Citations per field
00.5×1.6×
Saravanabavaan Suntharalingam · 1×
Citations per year

Countries citing papers authored by Michael Puesken

Since Specialization
Citations

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

Fields of papers citing papers by Michael Puesken

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Michael Puesken

This figure shows the co-authorship network connecting the top 25 collaborators of Michael Puesken. A scholar is included among the top collaborators of Michael Puesken 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 Michael Puesken. Michael Puesken 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 4
2 8
3 4
4 4
5 1
6 8
7 30
8 2
9 6
10
Beurteilung einer Lymphknoten-Metastasierung beim NSCLC – 3D-Parameter ergänzen die PET-CT nicht
5
11 13
12 6
13 15
14 20
15 18
16 26
17 34
18 5
19 9
20 31

About Michael Puesken

Michael Puesken is a scholar working on Radiology, Nuclear Medicine and Imaging, Pulmonary and Respiratory Medicine and Hepatology, having authored 31 papers that have together received 428 indexed citations. Recurring topics across this work include Radiomics and Machine Learning in Medical Imaging (11 papers), Medical Imaging Techniques and Applications (10 papers) and Lung Cancer Diagnosis and Treatment (7 papers). The work is most often cited by research in Radiology, Nuclear Medicine and Imaging (225 citations), Pulmonary and Respiratory Medicine (115 citations) and Biomedical Engineering (150 citations). Michael Puesken has collaborated with scholars based in Germany, Switzerland and United States. Frequent co-authors include Walter Heindel, Johannes Weßling, David Maintz, Boris Buerke, Harald Seifarth, Matthias Weckesser, Thorsten Persigehl, Carola Heneweer, Holger Grüll and Sin Yuin Yeo. Their work appears in journals such as American Journal of Roentgenology, European Radiology and Investigative 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.

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