Ronald Chan

51 papers receiving 1.2k citations

Ronald Chan's Hit Papers

Deep Learning in Breast Cancer Imaging: A Decade of Progress and Future Directions 2024 · 76 citations
760+1Years since publication255075

Peers

Ronald Chan
Comparison fields: 5 of 110
  • Hepatology 92
  • Cancer Research 172
  • Immunology 200
  • Health Informatics 11
  • Immunology and Allergy 44
Replace Dorina Gui with:
Dorina Gui United States
Zhen Han China
Xiaobo Zhou United States
Antonella Spila Italy
Tingbo Liang China
Jin Roh South Korea
Marieta Toma Germany
Yu Sun China
Soomin Ahn South Korea
Alexander H. Boag Canada
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Countries citing papers authored by Ronald Chan

Since Specialization
Citations

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

Fields of papers citing papers by Ronald Chan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 55 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2013179
2
The matrix metalloproteinase matrilysin influences early-stage mammary tumorigenesis.
1998133
3 2015101
4 201676
5
Deep Learning in Breast Cancer Imaging: A Decade of Progress and Future Directions
Hit paper breakdown →
202476
6 202272
7 201863
8 201945
9 199734
10 201633
11 202033
12 201430
13 202129
14 202027
15 202127
16 202119
17 201418
18 201318
19 202217
20 202215

About Ronald Chan

Ronald Chan is a scholar working on Pulmonary and Respiratory Medicine, Oncology, Artificial Intelligence, Radiology, Nuclear Medicine and Imaging and Molecular Biology, having authored 55 papers that have together received 1.2k indexed citations. Recurring topics across this work include AI in cancer detection (8 papers), Radiomics and Machine Learning in Medical Imaging (7 papers), Gut microbiota and health (2 papers), Bladder and Urothelial Cancer Treatments (2 papers), Iron Metabolism and Disorders (2 papers), Adipokines, Inflammation, and Metabolic Diseases (2 papers), Bacterial Identification and Susceptibility Testing (2 papers) and Cancer Immunotherapy and Biomarkers (2 papers). The work is most often cited by research in Hepatology (92 citations), Cancer Research (172 citations), Immunology (200 citations), Health Informatics (11 citations) and Immunology and Allergy (44 citations). Ronald Chan has collaborated with scholars based in Hong Kong, China and Canada. Frequent co-authors include Laura A. Rudolph‐Owen, Lynn M. Matrisian, William J. Muller, Aito Ueno, Subrata Ghosh, Ka‐Fai To, Miriam Fort Gasia, Paul L. Beck, Herman W. Barkema and Marietta Iacucci. Their work appears in journals such as Inflammatory Bowel Diseases, Pathology, Cancer Cytopathology, Nature Communications and Advanced Science.

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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