Mohammad Alrawashdeh

735 total citations · 1 hit paper
34 papers, 456 citations indexed

About

Mohammad Alrawashdeh is a scholar working on Surgery, Cardiology and Cardiovascular Medicine and Epidemiology. According to data from OpenAlex, Mohammad Alrawashdeh has authored 34 papers receiving a total of 456 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Surgery, 8 papers in Cardiology and Cardiovascular Medicine and 8 papers in Epidemiology. Recurrent topics in Mohammad Alrawashdeh's work include Acute Myocardial Infarction Research (7 papers), Transplantation: Methods and Outcomes (6 papers) and Cardiac electrophysiology and arrhythmias (4 papers). Mohammad Alrawashdeh is often cited by papers focused on Acute Myocardial Infarction Research (7 papers), Transplantation: Methods and Outcomes (6 papers) and Cardiac electrophysiology and arrhythmias (4 papers). Mohammad Alrawashdeh collaborates with scholars based in United States, Jordan and Canada. Mohammad Alrawashdeh's co-authors include Salah S. Al‐Zaiti, Christian Martin‐Gill, Clifton W. Callaway, Annette DeVito Dabbs, Ziad Faramand, Susan M. Sereika, Ervin Sejdić, Mi‐Kyung Song, Mary Amanda Dew and Joseph M. Pilewski and has published in prestigious journals such as Nature Medicine, SHILAP Revista de lepidopterología and PLoS ONE.

In The Last Decade

Mohammad Alrawashdeh

31 papers receiving 446 citations

Hit Papers

Machine learning for ECG diagnosis and risk stratificatio... 2023 2026 2024 2025 2023 40 80 120

Peers

Mohammad Alrawashdeh
Comparison fields: 5 of 88
  • Cardiology and Cardiovascular Medicine 166
  • Surgery 89
  • Epidemiology 67
  • Transplantation 60
  • Radiology, Nuclear Medicine and Imaging 56
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Citations per field, relative to Mohammad Alrawashdeh
Mohammad Alrawashdeh · 1×
Citations per year, relative to Mohammad Alrawashdeh
Mohammad Alrawashdeh · 1×

Countries citing papers authored by Mohammad Alrawashdeh

Since Specialization
Citations

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

Fields of papers citing papers by Mohammad Alrawashdeh

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Mohammad Alrawashdeh

This figure shows the co-authorship network connecting the top 25 collaborators of Mohammad Alrawashdeh. A scholar is included among the top collaborators of Mohammad Alrawashdeh 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 Mohammad Alrawashdeh. Mohammad Alrawashdeh 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
# Work Indexed citations
1 0
2 5
3
Machine learning for ECG diagnosis and risk stratification of occlusion myocardial infarction breakdown →
134
4 19
5 1
6 2
7 18
8 3
9 1
10 2
11 1
12 11
13 1
14
PREDICTION OF CONCRETE MIX COMPRESSIVE STRENGTH USING STATISTICAL LEARNING MODELS
4
15 24
16 6
17 9
18 20
19 91
20 24

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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