Heang‐Ping Chan

408 papers and 11.4k indexed citations i.

About

Heang‐Ping Chan is a scholar working on Radiology, Nuclear Medicine and Imaging, Artificial Intelligence and Pulmonary and Respiratory Medicine. According to data from OpenAlex, Heang‐Ping Chan has authored 408 papers receiving a total of 11.4k indexed citations (citations by other indexed papers that have themselves been cited), including 288 papers in Radiology, Nuclear Medicine and Imaging, 217 papers in Artificial Intelligence and 197 papers in Pulmonary and Respiratory Medicine. Recurrent topics in Heang‐Ping Chan’s work include AI in cancer detection (202 papers), Radiomics and Machine Learning in Medical Imaging (159 papers) and Digital Radiography and Breast Imaging (147 papers). Heang‐Ping Chan is often cited by papers focused on AI in cancer detection (202 papers), Radiomics and Machine Learning in Medical Imaging (159 papers) and Digital Radiography and Breast Imaging (147 papers). Heang‐Ping Chan collaborates with scholars based in United States, China and Thailand. Heang‐Ping Chan's co-authors include Lubomir M. Hadjiiski, Berkman Sahiner, Mark A. Helvie, Nicholas Petrick, Ravi K. Samala, Chuan Zhou, Mitchell M. Goodsitt, Jun Wei, Kunio Doi and Dorit D. Adler and has published in prestigious journals such as Scientific Reports, Radiology and IEEE Transactions on Medical Imaging.

In The Last Decade

Co-authorship network of co-authors of Heang‐Ping Chan i

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.

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).

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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