Thomas Weikert

1.2k citations
41 papers · 837 · h-index 17

Impact in

Papers in

Thomas Weikert

39 papers receiving 825 citations

Peers

Thomas Weikert
Comparison fields: 5 of 87
  • Health Informatics 114
  • Internal Medicine 107
  • Radiology, Nuclear Medicine and Imaging 329
  • Critical Care and Intensive Care Medicine 48
  • Pulmonary and Respiratory Medicine 140
Replace Jae‐Kwang Lim with:
Jae‐Kwang Lim South Korea
Christopher J. Roth United States
Reza Arsanjani United States
Sohail Contractor United States
Bernardo C. Bizzo United States
Joshy Cyriac Switzerland
Riccardo Cau Italy
Dharshan Vummidi United States
Nathaniel Swinburne United States
Elizabeth Le United Kingdom
Thomas Weikert relative to Jae‐Kwang Lim South Korea Jae‐Kwang Lim's profile →
Citations per field
00.5×3.9×
Jae‐Kwang Lim · 1×
Citations per year

Countries citing papers authored by Thomas Weikert

Since Specialization
Citations

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

Fields of papers citing papers by Thomas Weikert

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 41 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2020108
2 202071
3 201863
4 202262
5 202143
6 201942
7 202040
8 202233
9 202130
10 201327
11 202022
12 202022
13 202120
14 202020
15 201919
16 202217
17 202116
18 202115
19 202015
20 202315

About Thomas Weikert

Thomas Weikert is a scholar working on Radiology, Nuclear Medicine and Imaging, Pulmonary and Respiratory Medicine, Epidemiology, Biomedical Engineering and Cardiology and Cardiovascular Medicine, having authored 41 papers that have together received 837 indexed citations. Recurring topics across this work include Radiomics and Machine Learning in Medical Imaging (10 papers), Medical Imaging Techniques and Applications (5 papers), MRI in cancer diagnosis (3 papers), Advanced X-ray and CT Imaging (3 papers), Radiology practices and education (3 papers), COVID-19 diagnosis using AI (3 papers), Lung Cancer Diagnosis and Treatment (3 papers) and Venous Thromboembolism Diagnosis and Management (2 papers). The work is most often cited by research in Health Informatics (114 citations), Internal Medicine (107 citations), Radiology, Nuclear Medicine and Imaging (329 citations), Critical Care and Intensive Care Medicine (48 citations) and Pulmonary and Respiratory Medicine (140 citations). Thomas Weikert has collaborated with scholars based in Switzerland, Germany and United States. Frequent co-authors include Bram Stieltjes, Alexander Sauter, Jens Bremerich, Gregor Sommer, David Winkel, Daniel T. Boll, Joshy Cyriac, Tobias Heye, Shan Yang and Kristine A. Blackham. Their work appears in journals such as European Journal of Radiology, European Radiology, Contrast Media & Molecular Imaging, Investigative Radiology and Korean Journal of 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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