Kay See Tan

181 papers and 3.6k indexed citations i.

About

Kay See Tan is a scholar working on Pulmonary and Respiratory Medicine, Surgery and Oncology. According to data from OpenAlex, Kay See Tan has authored 181 papers receiving a total of 3.6k indexed citations (citations by other indexed papers that have themselves been cited), including 93 papers in Pulmonary and Respiratory Medicine, 67 papers in Surgery and 38 papers in Oncology. Recurrent topics in Kay See Tan’s work include Lung Cancer Diagnosis and Treatment (53 papers), Lung Cancer Treatments and Mutations (39 papers) and Esophageal Cancer Research and Treatment (30 papers). Kay See Tan is often cited by papers focused on Lung Cancer Diagnosis and Treatment (53 papers), Lung Cancer Treatments and Mutations (39 papers) and Esophageal Cancer Research and Treatment (30 papers). Kay See Tan collaborates with scholars based in United States, Japan and China. Kay See Tan's co-authors include Prasad S. Adusumilli, David R. Jones, Takashi Eguchi, William D. Travis, Matthew J. Bott, Manjit S. Bains, Daniela Molena, Daniel F. Heitjan, Natasha Rekhtman and Stephen M. Pastores and has published in prestigious journals such as Journal of Clinical Oncology, PLoS ONE and JNCI Journal of the National Cancer Institute.

In The Last Decade

Co-authorship network of co-authors of Kay See Tan i

Fields of papers citing papers by Kay See Tan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Kay See Tan. 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 Kay See Tan. The network helps show where Kay See Tan may publish in the future.

Countries citing papers authored by Kay See Tan

Since Specialization
Citations

This map shows the geographic impact of Kay See Tan'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 Kay See Tan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Kay See Tan 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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2025