B. Wein

2.3k citations
90 papers · 1.5k · h-index 17

Impact in

Papers in

B. Wein

86 papers receiving 1.4k citations

Peers

B. Wein
Comparison fields: 5 of 111
  • Computer Vision and Pattern Recognition 710
  • Artificial Intelligence 364
  • Radiology, Nuclear Medicine and Imaging 230
  • Speech and Hearing 58
  • Internal Medicine 27
Replace Akira Furukawa with:
Akira Furukawa Japan
Premal A. Patel United Kingdom
Lynn S. Broderick United States
Oğuz Dıcle Türkiye
Linda K. Olson United States
Steven C. Horii United States
Hiroyuki Yoshida United States
Eva M. van Rikxoort Netherlands
Saher Burhan Shaker Denmark
Mats Holmström Sweden
B. Wein relative to Akira Furukawa Japan Akira Furukawa's profile →
Citations per field
00.5×9.7×
Akira Furukawa · 1×
Citations per year

Countries citing papers authored by B. Wein

Since Specialization
Citations

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

Fields of papers citing papers by B. Wein

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 90 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2004213
2 2005149
3 2002105
4 2003103
5 199391
6 199780
7 199979
8 200355
9 200137
10 200733
11 200531
12 199130
13 199122
14 200022
15 200320
16 200018
17 199417
18
[Ultrasound study of disorders of coordination in tongue movement in swallowing].
198815
19 200015
20 199313

About B. Wein

B. Wein is a scholar working on Computer Vision and Pattern Recognition, Pulmonary and Respiratory Medicine, Radiology, Nuclear Medicine and Imaging, Artificial Intelligence and Physiology, having authored 90 papers that have together received 1.5k indexed citations. Recurring topics across this work include Image Retrieval and Classification Techniques (19 papers), Voice and Speech Disorders (10 papers), Advanced Image and Video Retrieval Techniques (9 papers), AI in cancer detection (9 papers), Dysphagia Assessment and Management (8 papers), Tracheal and airway disorders (8 papers), Radiomics and Machine Learning in Medical Imaging (7 papers) and Digital Radiography and Breast Imaging (6 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (710 citations), Artificial Intelligence (364 citations), Radiology, Nuclear Medicine and Imaging (230 citations), Speech and Hearing (58 citations) and Internal Medicine (27 citations). B. Wein has collaborated with scholars based in Germany, United States and Netherlands. Frequent co-authors include Thomas Lehmann, Henning Schubert, Daniel Keysers, Michael Kohnen, Hermann Ney, Klaus Spitzer, Mark Oliver Güld, Christian Thies, Benedikt Fischer and Joerg Bredno. Their work appears in journals such as RöFo - Fortschritte auf dem Gebiet der Röntgenstrahlen und der bildgebenden Verfahren, Investigative Radiology, Ultraschall in der Medizin - European Journal of Ultrasound, International Journal of Colorectal Disease and Journal of Magnetic Resonance Imaging.

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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