David S. Guttery

5.2k citations
65 papers · 2.7k indexed · 1 hit paper · h-index 30

Impact in

Papers in

David S. Guttery

65 papers receiving 2.7k citations

Hit Papers

Improved Breast Cancer Classification Through Combining Graph Convolutional Network and Convolutional Neural Network 2020 · 260 citations
260202020262022202450100150200250

Peers

David S. Guttery
Comparison fields: 5 of 152
  • Cancer Research 983
  • Oncology 663
  • Parasitology 126
  • Radiology, Nuclear Medicine and Imaging 346
  • Pathology and Forensic Medicine 253
Replace Shaofeng Yan with:
Shaofeng Yan United States
Vani Santosh India
Ying Chi China
Charles‐Antoine Dutertre Singapore
Gabriele Campanella United States
Augusto Silva Portugal
Juan Carlos Caicedo United States
Jun S. Wei United States
Smita Krishnaswamy United States
Ivan G. Costa Germany
David S. Guttery relative to Shaofeng Yan United States Shaofeng Yan's profile →
Citations per field
00.5×4.9×
Shaofeng Yan · 1×
Citations per year

Countries citing papers authored by David S. Guttery

Since Specialization
Citations

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

Fields of papers citing papers by David S. Guttery

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

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

All Works

20 of 20 papers shown
#Work
1 20244
2 20236
3 20232
4 20236
5 20228
6 20229
7 202113
8 202116
9 20205
10 202052
11 20202
12 202061
13 202041
14 202044
15 202031
16 201992
17 201838
18 201828
19 2016171
20 201028

About David S. Guttery

David S. Guttery is a scholar working on Cancer Research, Oncology, Neurology, Pathology and Forensic Medicine and Virology, having authored 65 papers that have together received 2.7k indexed citations. Recurring topics across this work include Cancer Genomics and Diagnostics (25 papers), Cancer Cells and Metastasis (14 papers), Genetic factors in colorectal cancer (13 papers), Malaria Research and Control (13 papers), Invertebrate Immune Response Mechanisms (8 papers), Radiomics and Machine Learning in Medical Imaging (8 papers), AI in cancer detection (7 papers) and Microtubule and mitosis dynamics (6 papers). The work is most often cited by research in Cancer Research (983 citations), Oncology (663 citations), Parasitology (126 citations), Radiology, Nuclear Medicine and Imaging (346 citations) and Pathology and Forensic Medicine (253 citations). David S. Guttery has collaborated with scholars based in United Kingdom, Saudi Arabia and China. Frequent co-authors include Yudong Zhang, Shuihua Wang‎, Jacqui Shaw, Karen Page, R. Charles Coombes, Rita Tewari, Anthony A. Holder, J. M. Górriz, Suresh Chandra Satapathy and Justin Stebbing. Their work appears in journals such as PLoS Pathogens, British Journal of Cancer, Breast Cancer Research, PLoS ONE and Life Science Alliance.

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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