Queenie Lau

529 citations
13 papers · 260 indexed · h-index 8
Topics
Glioma Diagnosis and Treatment (7 papers)Meningioma and schwannoma management (6 papers)Pituitary Gland Disorders and Treatments (3 papers)

In The Last Decade

Queenie Lau

12 papers receiving 255 citations

Peers

Queenie Lau
Comparison fields: 5 of 40
  • Genetics 195
  • Endocrinology, Diabetes and Metabolism 157
  • Epidemiology 102
  • Surgery 67
  • Pulmonary and Respiratory Medicine 37
Replace Varvara Vlassopoulou with:
Varvara Vlassopoulou Greece
Dieter Haller Switzerland
Humberto Uribe Canada
Sunil Jeswani United States
Stefania Acerno Italy
Emilija Manojlović-Gačić Serbia
Christian Ogasawara United States
Jochen B. Bader Germany
Márcio Carlos Machado Brazil
Masaharu Yasue Japan
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Citations per field
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Varvara Vlassopoulou · 1×
Citations per year

Countries citing papers authored by Queenie Lau

Since Specialization
Citations

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

Fields of papers citing papers by Queenie Lau

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Queenie Lau. 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 Queenie Lau. The network helps show where Queenie Lau may publish in the future.

Co-authorship network of co-authors of Queenie Lau

This figure shows the co-authorship network connecting the top 25 collaborators of Queenie Lau. A scholar is included among the top collaborators of Queenie Lau based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Queenie Lau. Queenie Lau is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

13 of 13 papers shown
#WorkIndexed citations
1
Development of a novel questionnaire to assess knowledge, attitude and practice towards medical disorders in pregnancy among clinicians.
1
2
Association of dengue serotypes and its complications: a retrospective cohort study.
1
3 1
4 0
5 10
6 31
7 43
8 29
9 76
10 45
11 9
12 1
13 13

About Queenie Lau

Queenie Lau is a scholar working on Genetics, Neurology and Endocrinology, Diabetes and Metabolism, having authored 13 papers that have together received 260 indexed citations. Recurring topics across this work include Glioma Diagnosis and Treatment (7 papers), Meningioma and schwannoma management (6 papers) and Pituitary Gland Disorders and Treatments (3 papers). The work is most often cited by research in Genetics (195 citations), Endocrinology, Diabetes and Metabolism (157 citations) and Epidemiology (102 citations). Queenie Lau has collaborated with scholars based in Australia, Canada and United States. Frequent co-authors include Bernd W. Scheithauer, Kálmán Kovács, Ricardo V. Lloyd, Éva Horváth, Luis V. Syro, Sandeep Bhuta, Charlie Hsu, Humberto Uribe, Ricardo R. González and León Darío Ortiz. Their work appears in journals such as Cancer, Journal of Neuro-Oncology and Pathology.

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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