F. W. Samuelson

4.4k citations
53 papers · 668 · h-index 11

Impact in

Papers in

F. W. Samuelson

47 papers receiving 655 citations

Peers

F. W. Samuelson
Comparison fields: 5 of 100
  • Health Informatics 21
  • Radiology, Nuclear Medicine and Imaging 205
  • Pulmonary and Respiratory Medicine 150
  • Artificial Intelligence 157
  • Cancer Research 62
Replace Gudrun Zahlmann with:
Gudrun Zahlmann Germany
Elodia B. Cole United States
R. Vanguri United States
Safoora Yousefi United States
Guy Nir Canada
Jason W. Chan United States
Alessandro Stefano Italy
Kazuma Kobayashi Japan
Te-Cheng Hsu Taiwan
Wentian Guo China
F. W. Samuelson relative to Gudrun Zahlmann Germany Gudrun Zahlmann's profile →
Citations per field
00.5×3.3×
Gudrun Zahlmann · 1×
Citations per year

Countries citing papers authored by F. W. Samuelson

Since Specialization
Citations

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

Fields of papers citing papers by F. W. Samuelson

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by F. W. Samuelson. 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 F. W. Samuelson. The network helps show where F. W. Samuelson may publish in the future.

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 53 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2010158
2 2018152
3 200666
4 200949
5 201430
6 200726
7 201323
8 201720
9 201614
10 201811
11 201610
12 20209
13 20199
14 20138
15 20147
16 20095
17 20135
18 20134
19 20114
20 20134

About F. W. Samuelson

F. W. Samuelson is a scholar working on Artificial Intelligence, Radiology, Nuclear Medicine and Imaging, Pulmonary and Respiratory Medicine, Statistics and Probability and Statistics, Probability and Uncertainty, having authored 53 papers that have together received 668 indexed citations. Recurring topics across this work include Digital Radiography and Breast Imaging (9 papers), AI in cancer detection (9 papers), Medical Imaging Techniques and Applications (8 papers), Statistical Methods and Inference (6 papers), Reliability and Agreement in Measurement (5 papers), Statistical Methods and Bayesian Inference (4 papers), Radiomics and Machine Learning in Medical Imaging (3 papers) and Statistical Methods in Clinical Trials (3 papers). The work is most often cited by research in Health Informatics (21 citations), Radiology, Nuclear Medicine and Imaging (205 citations), Pulmonary and Respiratory Medicine (150 citations), Artificial Intelligence (157 citations) and Cancer Research (62 citations). F. W. Samuelson has collaborated with scholars based in United States, Spain and Thailand. Frequent co-authors include Nicholas Petrick, Brandon D. Gallas, Rongping Zeng, Kyle J. Myers, Aldo Badano, Stephen J. Glick, Diksha Sharma, Andreu Badal, Christian Graff and Robert F. Wagner. Their work appears in journals such as Academic Radiology, Medical Physics, Statistical Methods in Medical Research, BMC Medical Research Methodology and Journal of the Optical Society of America A.

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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