PC Ng

947 citations
20 papers · 781 · h-index 13

Impact in

    • Dermatology and Skin Diseases
    • SARS-CoV-2 and COVID-19 Research
    • COVID-19 Clinical Research Studies
    • Viral gastroenteritis research and epidemiology

Papers in

PC Ng

20 papers receiving 716 citations

Peers

PC Ng
Comparison fields: 5 of 82
  • Dermatology 159
  • Infectious Diseases 260
  • Immunology and Allergy 70
  • Modeling and Simulation 44
  • Obstetrics and Gynecology 36
Replace Paolo D’Avino with:
Paolo D’Avino United States
Kurtuluş Aksu Türkiye
James G. Easton United States
Camille Rolland‐Debord France
Bianca Laura Cinicola Italy
Hsi-en Ho United States
Tania Siahanidou Greece
Danna Moustafa United States
Marco Maglione Italy
Laura Petrarca Italy
PC Ng relative to Paolo D’Avino United States Paolo D’Avino's profile →
Citations per field
00.5×1.5×2.2×
Paolo D’Avino · 1×
Citations per year

Countries citing papers authored by PC Ng

Since Specialization
Citations

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

Fields of papers citing papers by PC Ng

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 24 scholars most cited alongside PC Ng, 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 PC Ng Line = papers co-authored together PC Ng links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 2003337
2 200776
3 200669
4 199839
5 200334
6 200934
7 200128
8 199727
9 199625
10 200319
11 200217
12 199817
13 199714
14 200411
15 19969
16 19979
17 19987
18 20015
19 19963
20 19961

About PC Ng

PC Ng is a scholar working on Dermatology, Pediatrics, Perinatology and Child Health, Pulmonary and Respiratory Medicine, Cardiology and Cardiovascular Medicine and Epidemiology, having authored 20 papers that have together received 781 indexed citations. Recurring topics across this work include Neonatal Respiratory Health Research (3 papers), Dermatology and Skin Diseases (3 papers), COVID-19 Clinical Research Studies (2 papers), Respiratory viral infections research (2 papers), Prenatal Screening and Diagnostics (2 papers), Cardiovascular Conditions and Treatments (2 papers), SARS-CoV-2 and COVID-19 Research (2 papers) and Neonatal and fetal brain pathology (2 papers). The work is most often cited by research in Dermatology (159 citations), Infectious Diseases (260 citations), Immunology and Allergy (70 citations), Modeling and Simulation (44 citations) and Obstetrics and Gynecology (36 citations). PC Ng has collaborated with scholars based in Hong Kong and China. Frequent co-authors include TF Leung, TF Fok, Chi Kong Li, Mike Yat Wah Kwan, Chi‐Ho Lee, William Chi Wai Wong, Hung‐Kwan So, William W. Wong, Ka‐Lung Lam and M. Hjelm. Their work appears in journals such as Acta Paediatrica, British Journal of Dermatology, The Lancet, European Respiratory Journal and Orthodontics and Craniofacial Research.

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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