Anton S. Becker

4.7k citations
135 papers · 3.0k indexed · 1 hit paper · h-index 28

Anton S. Becker

127 papers receiving 3.0k citations

Hit Papers

Deep Learning in Mammography271201720262020202350100150200250

Peers

Anton S. Becker
Comparison fields: 5 of 143
  • Health Informatics 198
  • Radiology, Nuclear Medicine and Imaging 1.4k
  • Pulmonary and Respiratory Medicine 955
  • Cardiology and Cardiovascular Medicine 429
  • Artificial Intelligence 488
Replace Felix Nensa with:
Felix Nensa Germany
Nickolas Papanikolaou Greece
Ian F. Dunn United States
Vinay Duddalwar United States
Alexander Sauter Germany
Bettina Baeßler Germany
Omar Arnaout United States
Lorenzo Ugga Italy
Yin Xi United States
Robert M. Kwee Netherlands
Anton S. Becker relative to Felix Nensa Germany Felix Nensa's profile →
Citations per field
00.5×1.5×2.0×
Felix Nensa · 1×
Citations per year

Countries citing papers authored by Anton S. Becker

Since Specialization
Citations

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

Fields of papers citing papers by Anton S. Becker

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Anton S. Becker. 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 Anton S. Becker. The network helps show where Anton S. Becker may publish in the future.

Co-authorship network

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

All Works

20 of 20 papers shown
#Work
1 20250
2 20251
3 20240
4 20246
5 202411
6 20241
7 20232
8 20236
9 202210
10 20213
11 202184
12 202159
13 20208
14 202070
15 201918
16 2018108
17 20187
18
Artificial Intelligence und Machine Learning in der Medizin
20173
19 20161
20 201614

About Anton S. Becker

Anton S. Becker is a scholar working on Radiology, Nuclear Medicine and Imaging, Health Informatics, Pulmonary and Respiratory Medicine, Cardiology and Cardiovascular Medicine and Rheumatology, having authored 135 papers that have together received 3.0k indexed citations. Recurring topics across this work include Prostate Cancer Diagnosis and Treatment (26 papers), Radiomics and Machine Learning in Medical Imaging (25 papers), MRI in cancer diagnosis (24 papers), Prostate Cancer Treatment and Research (22 papers), Advanced MRI Techniques and Applications (17 papers), Medical Imaging Techniques and Applications (13 papers), Adipose Tissue and Metabolism (10 papers) and Advanced X-ray and CT Imaging (10 papers). The work is most often cited by research in Health Informatics (198 citations), Radiology, Nuclear Medicine and Imaging (1.4k citations), Pulmonary and Respiratory Medicine (955 citations), Cardiology and Cardiovascular Medicine (429 citations) and Artificial Intelligence (488 citations). Anton S. Becker has collaborated with scholars based in Switzerland, United States and United Kingdom. Frequent co-authors include Andreas Boss, Magda Marcon, Soleen Ghafoor, Moritz C. Wurnig, Thomas Frauenfelder, Irene A. Burger, Olivio F. Donati, Urs J. Muehlematter, Daniel Eberli and Cristina Rossi. Their work appears in journals such as European Journal of Radiology, European Radiology, PLoS ONE, Investigative Radiology and Academic 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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