Mike Sung

465 citations
18 papers · 318 · h-index 7

Impact in

  • Oncology top 10%
    • Cancer Immunotherapy and Biomarkers
    • Inflammatory Biomarkers in Disease Prognosis
    • Cancer survivorship and care
    • Lung Cancer Research Studies
    • Lung Cancer Treatments and Mutations
    • Lung Cancer Diagnosis and Treatment

Papers in

    • Lung Cancer Treatments and Mutations 9
    • Lung Cancer Diagnosis and Treatment 2
    • Cancer Immunotherapy and Biomarkers 4
    • Lung Cancer Research Studies 3
    • Colorectal Cancer Treatments and Studies 2

Mike Sung

16 papers receiving 312 citations

Peers

Mike Sung
Comparison fields: 5 of 58
  • Oncology 234
  • Pulmonary and Respiratory Medicine 149
  • Cancer Research 54
  • Otorhinolaryngology 7
  • Pediatrics, Perinatology and Child Health 31
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Citations per field
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Citations per year

Countries citing papers authored by Mike Sung

Since Specialization
Citations

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

Fields of papers citing papers by Mike Sung

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

18 of 18 papers shown
#Work
1 2018102
2 201773
3 201647
4 202031
5 202023
6 202211
7 20189
8 20165
9 20204
10 20174
11 20213
12 20192
13 20201
14 20241
15 20171
16 20191
17
A technology for corrosion protection
20110
18 20240

About Mike Sung

Mike Sung is a scholar working on Pulmonary and Respiratory Medicine, Oncology, Cancer Research, Artificial Intelligence and Radiology, Nuclear Medicine and Imaging, having authored 18 papers that have together received 318 indexed citations. Recurring topics across this work include Lung Cancer Treatments and Mutations (9 papers), Cancer Immunotherapy and Biomarkers (4 papers), Cancer Genomics and Diagnostics (4 papers), Lung Cancer Research Studies (3 papers), Radiomics and Machine Learning in Medical Imaging (3 papers), Colorectal Cancer Treatments and Studies (2 papers), Natural Language Processing Techniques (2 papers) and Lung Cancer Diagnosis and Treatment (2 papers). The work is most often cited by research in Oncology (234 citations), Pulmonary and Respiratory Medicine (149 citations), Cancer Research (54 citations), Otorhinolaryngology (7 citations) and Pediatrics, Perinatology and Child Health (31 citations). Mike Sung has collaborated with scholars based in Canada, United Kingdom and United States. Frequent co-authors include Natasha B. Leighl, Frances A. Shepherd, Ronald Feld, Geoffrey Liu, Lisa W. Le, Penelope A. Bradbury, Leila Khoja, Catherine Labbé, Manjula Maganti and Alona Zer. Their work appears in journals such as Journal of Thoracic Oncology, Clinical Lung Cancer, Value in Health, Journal of Clinical Oncology and Lung Cancer.

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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