Stephen Daw

1.1k citations
46 papers · 712 · h-index 16

Impact in

Papers in

Stephen Daw

39 papers receiving 694 citations

Peers

Stephen Daw
Comparison fields: 5 of 51
  • Pathology and Forensic Medicine 402
  • Neurology 179
  • Radiology, Nuclear Medicine and Imaging 163
  • Oncology 182
  • Genetics 59
Replace Liang Guan with:
Liang Guan United States
Adrian R. Timothy United Kingdom
Victor Vishwanath Iyer Denmark
S Rehn Sweden
Leanne Berkahn New Zealand
Anne Lerberg Nielsen Denmark
HI Libshitz United States
St. Müller-Weihrich Germany
Raghava Kashyap India
Lars Kurch Germany
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Citations per field
00.5×5.4×
Liang Guan · 1×
Citations per year

Countries citing papers authored by Stephen Daw

Since Specialization
Citations

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

Fields of papers citing papers by Stephen Daw

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 46 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2010103
2 201268
3 201867
4 200058
5 201148
6 202036
7 201136
8 200734
9 201832
10 201031
11 201928
12 201227
13 202219
14 201317
15 201415
16 202115
17 201811
18 201310
19 20208
20 20066

About Stephen Daw

Stephen Daw is a scholar working on Pathology and Forensic Medicine, Oncology, Neurology, Pulmonary and Respiratory Medicine and Radiology, Nuclear Medicine and Imaging, having authored 46 papers that have together received 712 indexed citations. Recurring topics across this work include Lymphoma Diagnosis and Treatment (33 papers), CNS Lymphoma Diagnosis and Treatment (12 papers), Lung Cancer Treatments and Mutations (10 papers), Viral-associated cancers and disorders (7 papers), CAR-T cell therapy research (5 papers), Acute Lymphoblastic Leukemia research (4 papers), Chronic Lymphocytic Leukemia Research (4 papers) and Radiopharmaceutical Chemistry and Applications (3 papers). The work is most often cited by research in Pathology and Forensic Medicine (402 citations), Neurology (179 citations), Radiology, Nuclear Medicine and Imaging (163 citations), Oncology (182 citations) and Genetics (59 citations). Stephen Daw has collaborated with scholars based in United Kingdom, United States and Germany. Frequent co-authors include Ananth Shankar, Shonit Punwani, Stuart A. Taylor, Paul Humphries, Alan Bainbridge, Russell C. Dale, Moin A. Saleem, Michael J. Dillon, Sharon F. Hain and Steven Bandula. Their work appears in journals such as Blood, British Journal of Haematology, Hematological Oncology, HemaSphere and Journal of Clinical Oncology.

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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