Si‐Wa Chan

1.3k citations
44 papers · 879 · h-index 15

Impact in

Papers in

Si‐Wa Chan

41 papers receiving 863 citations

Peers

Si‐Wa Chan
Comparison fields: 5 of 91
  • Radiology, Nuclear Medicine and Imaging 530
  • Health Informatics 18
  • Artificial Intelligence 369
  • Pulmonary and Respiratory Medicine 296
  • Cancer Research 98
Replace Kanae K. Miyake with:
Kanae K. Miyake Japan
Xinming Zhao China
Jun Cheng China
Katharina Holland Netherlands
Zhenchao Tang China
Goshi Oda Japan
Kazunori Kubota Japan
Raffaella Massafra Italy
Si‐Wa Chan relative to Kanae K. Miyake Japan Kanae K. Miyake's profile →
Citations per field
00.5×1.5×
Kanae K. Miyake · 1×
Citations per year

Countries citing papers authored by Si‐Wa Chan

Since Specialization
Citations

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

Fields of papers citing papers by Si‐Wa Chan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 44 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2008137
2 2010110
3 2020102
4 201977
5 201051
6 202050
7 201346
8 201031
9 201131
10 201730
11 201219
12 200919
13 201616
14 200714
15 200914
16 201013
17 201912
18 202112
19 201610
20 20189

About Si‐Wa Chan

Si‐Wa Chan is a scholar working on Radiology, Nuclear Medicine and Imaging, Pulmonary and Respiratory Medicine, Artificial Intelligence, Surgery and Molecular Biology, having authored 44 papers that have together received 879 indexed citations. Recurring topics across this work include AI in cancer detection (18 papers), Digital Radiography and Breast Imaging (14 papers), MRI in cancer diagnosis (13 papers), Medical Imaging Techniques and Applications (8 papers), Radiomics and Machine Learning in Medical Imaging (6 papers), Advanced MRI Techniques and Applications (4 papers), Venous Thromboembolism Diagnosis and Management (3 papers) and Infective Endocarditis Diagnosis and Management (3 papers). The work is most often cited by research in Radiology, Nuclear Medicine and Imaging (530 citations), Health Informatics (18 citations), Artificial Intelligence (369 citations), Pulmonary and Respiratory Medicine (296 citations) and Cancer Research (98 citations). Si‐Wa Chan has collaborated with scholars based in Taiwan, United States and South Korea. Frequent co-authors include Jeon‐Hor Chen, Min‐Ying Su, Orhan Nalcioğlu, Muqing Lin, Rita S. Mehta, Ke Nie, Daniel Chow, Shadfar Bahri, Dah‐Cherng Yeh and Hon J. Yu. Their work appears in journals such as Medical Physics, Academic Radiology, International journal of cardiac imaging, Magnetic Resonance Imaging and Biomarker 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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