Stephen Yip

144 papers receiving 2.9k citations

Peers

Stephen Yip
Comparison fields: 5 of 130
  • Genetics 496
  • Health Informatics 49
  • Cancer Research 505
  • Obstetrics and Gynecology 152
  • Pulmonary and Respiratory Medicine 641
Replace Shumpei Ishikawa with:
Shumpei Ishikawa Japan
David Fenstermacher United States
Inti Zlobec Switzerland
Håvard E. Danielsen Norway
Maximilian Niyazi Germany
Priti Lal United States
Arvind Rao United States
Kazuhiko Ogawa Japan
Bassam Abdulkarim Canada
Dongsheng Gu China
Stephen Yip relative to Shumpei Ishikawa Japan Shumpei Ishikawa's profile →
Citations per field
00.5×4.9×
Shumpei Ishikawa · 1×
Citations per year

Countries citing papers authored by Stephen Yip

Since Specialization
Citations

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

Fields of papers citing papers by Stephen Yip

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 153 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2010207
2 2011178
3 2019143
4 2016132
5 2012111
6 201988
7 201187
8 200985
9 201262
10 201861
11 202357
12 201956
13 201553
14 200352
15 201951
16 201350
17 201848
18 202146
19 202143
20 199142

About Stephen Yip

Stephen Yip is a scholar working on Pulmonary and Respiratory Medicine, Cancer Research, Oncology, Molecular Biology and Genetics, having authored 153 papers that have together received 2.9k indexed citations. Recurring topics across this work include Glioma Diagnosis and Treatment (31 papers), Cancer Genomics and Diagnostics (28 papers), Lung Cancer Treatments and Mutations (15 papers), Sarcoma Diagnosis and Treatment (10 papers), Pancreatic and Hepatic Oncology Research (7 papers), Cancer Cells and Metastasis (6 papers), Brain Metastases and Treatment (6 papers) and AI in cancer detection (6 papers). The work is most often cited by research in Genetics (496 citations), Health Informatics (49 citations), Cancer Research (505 citations), Obstetrics and Gynecology (152 citations) and Pulmonary and Respiratory Medicine (641 citations). Stephen Yip has collaborated with scholars based in Canada, United States and United Kingdom. Frequent co-authors include David N. Louis, Michael Jansen, Derek Wong, Steven J.M. Jones, Marco A. Marra, Amy Lum, Adrian Levine, Janessa Laskin, Jasleen Grewal and Poul H. Sorensen. Their work appears in journals such as Journal of Clinical Oncology, Neuro-Oncology, Molecular Case Studies, Modern Pathology and Canadian Journal of Neurological Sciences / Journal Canadien des Sciences Neurologiques.

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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