Sharon Saw

925 citations
40 papers · 541 · h-index 13

Impact in

    • SARS-CoV-2 and COVID-19 Research
    • SARS-CoV-2 detection and testing
    • COVID-19 Clinical Research Studies
  • Nephrology top 10%
    • Parathyroid Disorders and Treatments

Papers in

    • Hepatitis B Virus Studies 5
    • COVID-19 Clinical Research Studies 3
    • SARS-CoV-2 and COVID-19 Research 3
    • SARS-CoV-2 detection and testing 3

Sharon Saw

39 papers receiving 532 citations

Peers

Sharon Saw
Comparison fields: 5 of 87
  • Infectious Diseases 134
  • Nephrology 45
  • Hepatology 29
  • Pathology and Forensic Medicine 62
  • Endocrinology, Diabetes and Metabolism 45
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B. Baird United States
Cristóvão Luís Pitangueira Mangueira Brazil
Jianping Sun China
Diego Martínez‐Urbistondo Spain
Heshmatollah Shahbazian Iran
Eduardo Shahar Israel
Ana Esther Sirvent Spain
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Citations per field
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Citations per year

Countries citing papers authored by Sharon Saw

Since Specialization
Citations

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

Fields of papers citing papers by Sharon Saw

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 40 papers — load more, or switch the sort, to bring in the rest.

#Work
1 202066
2 200949
3 201249
4 202039
5 201031
6 202029
7 202026
8 201322
9 200020
10 201519
11 201119
12 199918
13 201315
14 200912
15 201212
16 201510
17 20149
18 20119
19 20159
20 20188

About Sharon Saw

Sharon Saw is a scholar working on Epidemiology, Infectious Diseases, Physiology, Nephrology and Pathology and Forensic Medicine, having authored 40 papers that have together received 541 indexed citations. Recurring topics across this work include Hepatitis B Virus Studies (5 papers), Clinical Laboratory Practices and Quality Control (5 papers), Chronic Kidney Disease and Diabetes (3 papers), COVID-19 Clinical Research Studies (3 papers), SARS-CoV-2 and COVID-19 Research (3 papers), SARS-CoV-2 detection and testing (3 papers), Hemoglobinopathies and Related Disorders (2 papers) and Vitamin D Research Studies (2 papers). The work is most often cited by research in Infectious Diseases (134 citations), Nephrology (45 citations), Hepatology (29 citations), Pathology and Forensic Medicine (62 citations) and Endocrinology, Diabetes and Metabolism (45 citations). Sharon Saw has collaborated with scholars based in Singapore, South Korea and Thailand. Frequent co-authors include Sunil Sethi, Sunil Sethi, Tar Choon Aw, Roland Jureen, Shaun Shi Yan Tan, Lizhen Ong, Tze Ping Loh, Karen Tan, Paul Anantharajah Tambyah and Ka Lip Chew. Their work appears in journals such as Pathology, BMJ Quality & Safety, Clinical Chemistry, Clinica Chimica Acta and Annals of Clinical Biochemistry International Journal of Laboratory Medicine.

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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