Laboratory of Data Discovery for Health

310 papers and 3.4k indexed citations i.

About

In recent decades, authors affiliated with Laboratory of Data Discovery for Health have published 310 papers, which have received a total of 3.4k indexed citations. Scholars at this organization have produced 152 papers in Infectious Diseases, 87 papers in Modeling and Simulation and 81 papers in Epidemiology on the topics of SARS-CoV-2 and COVID-19 Research (114 papers), COVID-19 epidemiological studies (87 papers) and COVID-19 Clinical Research Studies (65 papers). Their work is cited by papers focused on Infectious Diseases (2.1k citations), Epidemiology (652 citations) and Modeling and Simulation (649 citations). Authors at Laboratory of Data Discovery for Health collaborate with scholars in Hong Kong, United Kingdom and China and have published in prestigious journals including Nature, Science and Cell. Some of Laboratory of Data Discovery for Health's most productive authors include Benjamin J. Cowling, Eric H. Y. Lau, Carlos King Ho Wong, GM Leung, Peng Wu, Ian Chi Kei Wong, Esther W. Chan, Eric Yuk Fai Wan, Ivan Chi Ho Au and Celine Sze Ling Chui.

In The Last Decade

Fields of papers published by authors at Laboratory of Data Discovery for Health

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers affiliated with Laboratory of Data Discovery for Health at the time of their publication. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers affiliated with Laboratory of Data Discovery for Health at the time of their publication.

Countries citing scholars working at Laboratory of Data Discovery for Health

Since Specialization

Citations

This map shows the geographic impact of research produced by authors working at Laboratory of Data Discovery for Health. 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 papers produced at Laboratory of Data Discovery for Health with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Laboratory of Data Discovery for Health 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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