Lee Cooper

114 papers receiving 4.4k citations

Lee Cooper's Hit Papers

Deep learning enables robust assessment and selection of human blastocysts after in vitro fertilization 2019 · 285 citations
2850+2+5Years since publication200400600

Peers

Lee Cooper
Comparison fields: 5 of 167
  • Health Informatics 139
  • Biophysics 439
  • Genetics 739
  • Radiology, Nuclear Medicine and Imaging 1.2k
  • Cancer Research 522
Replace Xiaobo Zhou with:
Xiaobo Zhou United States
Raymond Y. Huang United States
Olivier Gevaert United States
Tahsin Kurç United States
Matija Snuderl United States
Kaustav Bera United States
Di Dong China
Kurt A. Schalper United States
Arvind Rao United States
Rivka R. Colen United States
Lee Cooper relative to Xiaobo Zhou United States Xiaobo Zhou's profile →
Citations per field
00.5×4.8×
Xiaobo Zhou · 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-authors

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

Showing the 20 most-cited of 120 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Predicting cancer outcomes from histology and genomics using convolutional networks
Hit paper breakdown →
2018666
2 2017289
3
Deep learning enables robust assessment and selection of human blastocysts after in vitro fertilization
Hit paper breakdown →
2019285
4 2012180
5 2013157
6 1999156
7 2017146
8 2017131
9 2013126
10 2010117
11 2017103
12 201789
13 201689
14 201384
15 201978
16 201575
17 201272
18 201268
19 202367
20 201864

About Lee Cooper

Lee Cooper is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Radiology, Nuclear Medicine and Imaging, Biophysics and Molecular Biology, having authored 120 papers that have together received 4.5k indexed citations. Recurring topics across this work include AI in cancer detection (35 papers), Cell Image Analysis Techniques (25 papers), Radiomics and Machine Learning in Medical Imaging (18 papers), Glioma Diagnosis and Treatment (18 papers), Medical Image Segmentation Techniques (15 papers), Digital Imaging for Blood Diseases (9 papers), Cancer Genomics and Diagnostics (7 papers) and Single-cell and spatial transcriptomics (5 papers). The work is most often cited by research in Health Informatics (139 citations), Biophysics (439 citations), Genetics (739 citations), Radiology, Nuclear Medicine and Imaging (1.2k citations) and Cancer Research (522 citations). Lee Cooper has collaborated with scholars based in United States, United Kingdom and Philippines. Frequent co-authors include Daniel J. Brat, David A. Gutman, Mohamed Amgad, Joel Saltz, Jun Kong, Safoora Yousefi, Pooya Mobadersany, Tahsin Kurç, José E. Velázquez Vega and Jill S. Barnholtz‐Sloan. Their work appears in journals such as Scientific Reports, Cancer Research, Modern Pathology, PLoS ONE 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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