Fadia Mayyas

1.1k citations
48 papers · 858 indexed · h-index 17
Topics
Cardiovascular Function and Risk Factors (5 papers)Fatty Acid Research and Health (5 papers)Lipoproteins and Cardiovascular Health (4 papers)

In The Last Decade

Fadia Mayyas

47 papers receiving 847 citations

Peers

Fadia Mayyas
Comparison fields: 5 of 120
  • Cardiology and Cardiovascular Medicine 284
  • Physiology 172
  • Molecular Biology 126
  • Endocrinology, Diabetes and Metabolism 113
  • Surgery 111
Replace Beatriz Martín‐Fernández with:
Beatriz Martín‐Fernández Spain
Liping Xu China
Deepmala Agarwal United States
Xiao‐Lian Shi China
Olivera Stanojlović Serbia
Nicholas Knight United Kingdom
Amr M. Abbas Egypt
Nada A. Sallam Egypt
Mei Qiu China
Quynh Nhu Dinh Australia
Fadia Mayyas relative to Beatriz Martín‐Fernández Spain Beatriz Martín‐Fernández's profile →
Citations per field
00.5×1.5×
Beatriz Martín‐Fernández · 1×
Citations per year

Countries citing papers authored by Fadia Mayyas

Since Specialization
Citations

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

Fields of papers citing papers by Fadia Mayyas

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Fadia Mayyas

This figure shows the co-authorship network connecting the top 25 collaborators of Fadia Mayyas. A scholar is included among the top collaborators of Fadia Mayyas 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 Fadia Mayyas. Fadia Mayyas is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
#WorkIndexed citations
1 1
2 1
3 1
4 2
5 2
6 4
7 13
8 6
9 14
10 9
11 26
12 25
13 52
14 13
15 67
16 16
17 6
18 63
19 41
20 24

About Fadia Mayyas

Fadia Mayyas is a scholar working on Behavioral Neuroscience, Biological Psychiatry and Cardiology and Cardiovascular Medicine, having authored 48 papers that have together received 858 indexed citations. Recurring topics across this work include Cardiovascular Function and Risk Factors (5 papers), Fatty Acid Research and Health (5 papers) and Lipoproteins and Cardiovascular Health (4 papers). The work is most often cited by research in Biological Psychiatry (48 citations), Cardiology and Cardiovascular Medicine (284 citations) and Behavioral Neuroscience (38 citations). Fadia Mayyas has collaborated with scholars based in Jordan, United States and Bahrain. Frequent co-authors include Karem H. Alzoubi, David R. Van Wagoner, Omar F. Khabour, Khalid S Ibrahim, John Barnard, Mina K. Chung, Mark Niebauer, A. Marc Gillinov, Andrew O. Zurick and Nizar M. Mhaidat. Their work appears in journals such as PLoS ONE, The American Journal of Cardiology and Cardiovascular 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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