Heang‐Ping Chan

18.5k citations
407 papers · 12.8k · 1 hit paper · h-index 60

Impact in

Papers in

Heang‐Ping Chan

397 papers receiving 12.3k citations

Heang‐Ping Chan's Hit Papers

Deep Learning in Medical Image Analysis 2020 · 483 citations
4830+2+4Years since publication100200300400

Peers

Heang‐Ping Chan
Comparison fields: 5 of 182
  • Radiology, Nuclear Medicine and Imaging 6.3k
  • Health Informatics 303
  • Artificial Intelligence 6.2k
  • Pulmonary and Respiratory Medicine 3.9k
  • Computer Vision and Pattern Recognition 2.6k
Replace Maryellen L. Giger with:
Maryellen L. Giger United States
Berkman Sahiner United States
Lubomir M. Hadjiiski United States
Francesco Ciompi Netherlands
Jianhua Yao United States
Ronald M. Summers United States
Geert Litjens Netherlands
Arnaud A. A. Setio Netherlands
Clara I. Sá‎nchez Netherlands
Jeroen van der Laak Netherlands
Heang‐Ping Chan relative to Maryellen L. Giger United States Maryellen L. Giger's profile →
Citations per field
00.5×1.5×
Maryellen L. Giger · 1×
Citations per year

Countries citing papers authored by Heang‐Ping Chan

Since Specialization
Citations

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

Fields of papers citing papers by Heang‐Ping Chan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 407 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Deep Learning in Medical Image Analysis
Hit paper breakdown →
2020483
2 1996310
3 1990273
4 2020238
5 1987235
6 1995234
7 2002224
8 2008213
9 2016211
10 2006211
11 1999188
12 2016181
13 2006175
14 2018175
15 1995159
16 2017158
17 1995157
18 1998155
19 2017154
20 1998154

About Heang‐Ping Chan

Heang‐Ping Chan is a scholar working on Radiology, Nuclear Medicine and Imaging, Artificial Intelligence, Pulmonary and Respiratory Medicine, Oncology and Biomedical Engineering, having authored 407 papers that have together received 12.8k indexed citations. Recurring topics across this work include AI in cancer detection (186 papers), Radiomics and Machine Learning in Medical Imaging (139 papers), Digital Radiography and Breast Imaging (132 papers), Medical Imaging Techniques and Applications (72 papers), Colorectal Cancer Screening and Detection (50 papers), Advanced X-ray and CT Imaging (45 papers), Lung Cancer Diagnosis and Treatment (31 papers) and Bladder and Urothelial Cancer Treatments (26 papers). The work is most often cited by research in Radiology, Nuclear Medicine and Imaging (6.3k citations), Health Informatics (303 citations), Artificial Intelligence (6.2k citations), Pulmonary and Respiratory Medicine (3.9k citations) and Computer Vision and Pattern Recognition (2.6k citations). Heang‐Ping Chan has collaborated with scholars based in United States, China and Thailand. Frequent co-authors include Lubomir M. Hadjiiski, Berkman Sahiner, Mark A. Helvie, Nicholas Petrick, Ravi K. Samala, Chuan Zhou, Mitchell M. Goodsitt, Jun Wei, Dorit D. Adler and Kunio Doi. Their work appears in journals such as Medical Physics, Radiology, Physics in Medicine and Biology, Academic Radiology and IEEE Transactions on Medical Imaging.

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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