Pamela Green

1.7k citations
30 papers · 1.2k indexed · h-index 19
  • Hepatology top 5%
    • Hepatitis C virus research 5
    • COVID-19 Clinical Research Studies 6
    • SARS-CoV-2 and COVID-19 Research 2
  • Oncology top 10%
    • COVID-19 and healthcare impacts 8
    • Colorectal Cancer Screening and Detection 6
  • Equine top 5%
  • Epidemiology top 10%
    • Liver Disease Diagnosis and Treatment 7
    • Hepatitis B Virus Studies 3
    • COVID-19 and Mental Health 4

Pamela Green

30 papers receiving 1.1k citations

Peers

Pamela Green
Comparison fields: 5 of 102
  • Hepatology 243
  • Infectious Diseases 344
  • Oncology 338
  • Equine 19
  • Epidemiology 353
Replace Nathanaël Lapidus with:
Nathanaël Lapidus France
Bhaskar Thakur India
Satoko Ohfuji Japan
Xin Cheng China
Hannah Chung Canada
Wang Zhou China
Ighovwerha Ofotokun United States
Shaofa Nie China
Xiao Gong China
Eric Aris Tanzania
Pamela Green relative to Nathanaël Lapidus France Nathanaël Lapidus's profile →
Citations per field
00.5×2.7×
Nathanaël Lapidus · 1×
Citations per year

Countries citing papers authored by Pamela Green

Since Specialization
Citations

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

Fields of papers citing papers by Pamela Green

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

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

All Works

20 of 20 papers shown
#Work
1 20237
2 202229
3 202111
4 202114
5 202062
6 202017
7 202032
8 2019138
9 201880
10 20188
11 201817
12 201716
13 201232
14 200955
15 200839
16 200844
17 200710
18 200342
19 199831
20 19833

About Pamela Green

Pamela Green is a scholar working on Hepatology, Equine and Oncology, having authored 30 papers that have together received 1.2k indexed citations. Recurring topics across this work include COVID-19 and healthcare impacts (8 papers), Liver Disease Diagnosis and Treatment (7 papers), Colorectal Cancer Screening and Detection (6 papers), COVID-19 Clinical Research Studies (6 papers), Hepatitis C virus research (5 papers), COVID-19 and Mental Health (4 papers), Hepatitis B Virus Studies (3 papers) and SARS-CoV-2 and COVID-19 Research (2 papers). The work is most often cited by research in Hepatology (243 citations), Infectious Diseases (344 citations) and Oncology (338 citations). Pamela Green has collaborated with scholars based in United States, South Africa and Canada. Frequent co-authors include Kristin Berry, George N. Ioannou, Jason A. Dominitz, Emily R. Locke, Ann M. O’Hare, Vincent S. Fan, McKenna C. Eastment, Javeed A. Shah, Kristina Crothers and Kathleen F. Kerr. Their work appears in journals such as JAMA, Annals of Internal Medicine and Gastroenterology.

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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