D. Teather

28 papers receiving 321 citations

Peers

D. Teather
Comparison fields: 5 of 92
  • Family Practice 16
  • Internal Medicine 15
  • Statistics and Probability 34
  • Radiology, Nuclear Medicine and Imaging 66
  • Human Factors and Ergonomics 7
Replace Eugenio Alberdi with:
Eugenio Alberdi United Kingdom
Taylor United States
Olga Medvedeva United States
Glenn D. Rennels United States
Alexandra Posekany Austria
Raymond Yee Canada
M. Hessinger Austria
Otto Rienhoff Germany
Manuel Luque Spain
Jingjing Gong China
D. Teather relative to Eugenio Alberdi United Kingdom Eugenio Alberdi's profile →
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Countries citing papers authored by D. Teather

Since Specialization
Citations

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

Fields of papers citing papers by D. Teather

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 18 scholars most cited alongside D. Teather, 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 D. Teather Line = papers co-authored together D. Teather links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 31 papers — load more, or switch the sort, to bring in the rest.

#Work
1 200274
2 199837
3 200036
4 197426
5 197419
6 197319
7 197719
8 198118
9 198514
10 198714
11 199012
12 198412
13
Subcutaneous heparin. A logical prophylaxis for deep vein thrombosis after myocardial infarction.
197812
14 198811
15 19829
16 19748
17 19888
18 19945
19 19825
20 19943

About D. Teather

D. Teather is a scholar working on Artificial Intelligence, Radiology, Nuclear Medicine and Imaging, Computer Vision and Pattern Recognition, Molecular Biology and Cardiology and Cardiovascular Medicine, having authored 31 papers that have together received 376 indexed citations. Recurring topics across this work include Venous Thromboembolism Diagnosis and Management (4 papers), Brain Tumor Detection and Classification (4 papers), Medical Image Segmentation Techniques (4 papers), Radiology practices and education (4 papers), Radiomics and Machine Learning in Medical Imaging (4 papers), Biomedical Text Mining and Ontologies (4 papers), AI in cancer detection (4 papers) and Medical Imaging Techniques and Applications (3 papers). The work is most often cited by research in Family Practice (16 citations), Internal Medicine (15 citations), Statistics and Probability (34 citations), Radiology, Nuclear Medicine and Imaging (66 citations) and Human Factors and Ergonomics (7 citations). D. Teather has collaborated with scholars based in United Kingdom, Ghana and Bangladesh. Frequent co-authors include G. H. du Boulay, Mike Sharples, A. Handley, Byron Jones, Jihong Wang, Peter Emerson, D. Plummer, Benedict du Boulay, P.R. Innocent and Anthony J. Handley. Their work appears in journals such as Neuroradiology, British Journal of Radiology, Statistics in Medicine, Methods of Information in Medicine and Medical Decision Making.

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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