Lee Cooper

17.2k citations
117 papers · 4.4k indexed · 2 hit papers · h-index 34

Lee Cooper

111 papers receiving 4.3k citations

Hit Papers

Deep learning enables robust assessment and selection of ...2722018202620202023200400600

Peers

Lee Cooper
Comparison fields: 5 of 172
  • Health Informatics 161
  • Biophysics 492
  • Genetics 811
  • Radiology, Nuclear Medicine and Imaging 1.5k
  • Cancer Research 663
Replace Olivier Gevaert with:
Olivier Gevaert United States
Raymond Y. Huang United States
Paul Koppel Netherlands
Tahsin Kurç United States
Metin N. Gürcan United States
Matija Snuderl United States
Yoganand Balagurunathan United States
Kaustav Bera United States
Benjamin Haibe‐Kains Canada
Arvind Rao United States
Lee Cooper relative to Olivier Gevaert United States Olivier Gevaert's profile →
Citations per field
00.5×3.8×
Olivier Gevaert · 1×
Citations per year

Countries citing papers authored by Lee Cooper

Since Specialization
Citations

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

Fields of papers citing papers by Lee Cooper

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

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

All Works

20 of 20 papers shown
#Work
1 20250
2 20250
3 20243
4 20242
5 20245
6 202314
7 202353
8 20239
9 20230
10 202127
11 202122
12 201974
13
Predicting cancer outcomes from histology and genomics using convolutional networksbreakdown →
2018646
14 2017100
15 2017283
16 201573
17 2012179
18 201118
19 201117
20
DESIGNING THE CONTROL AND SIMULATION OF EGR
19961

About Lee Cooper

Lee Cooper is a scholar working on Biophysics, Health Informatics and Orthodontics, having authored 117 papers that have together received 4.4k indexed citations. Recurring topics across this work include AI in cancer detection (39 papers), Cell Image Analysis Techniques (28 papers), Radiomics and Machine Learning in Medical Imaging (21 papers), Glioma Diagnosis and Treatment (19 papers), Medical Image Segmentation Techniques (16 papers), Digital Imaging for Blood Diseases (9 papers), Cancer Genomics and Diagnostics (9 papers) and Advanced MRI Techniques and Applications (7 papers). The work is most often cited by research in Health Informatics (161 citations), Biophysics (492 citations) and Genetics (811 citations). Lee Cooper has collaborated with scholars based in United States, United Kingdom and Spain. Frequent co-authors include Daniel J. Brat, David A. Gutman, Mohamed Amgad, Joel Saltz, Jun Kong, Safoora Yousefi, Pooya Mobadersany, Tahsin Kurç, Jill S. Barnholtz‐Sloan and José E. Velázquez Vega. Their work appears in journals such as Scientific Reports, Cancer Research, Modern Pathology, Laboratory Investigation and Caries Research.

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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