Hani Mowafi

44 papers receiving 1.0k citations

Hani Mowafi's Hit Papers

Prediction of In‐hospital Mortality in Emergency Department Patients With Sepsis: A Local Big Data–Driven, Machine Learning Approach 2015 · 361 citations
3610+3+7Years since publication100200300

Peers

Hani Mowafi
Comparison fields: 5 of 120
  • Health Informatics 30
  • Emergency Medical Services 130
  • Emergency Medicine 161
  • Family Practice 19
  • Health Information Management 45
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Citations per year

Countries citing papers authored by Hani Mowafi

Since Specialization
Citations

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

Fields of papers citing papers by Hani Mowafi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 46 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Prediction of In‐hospital Mortality in Emergency Department Patients With Sepsis: A Local Big Data–Driven, Machine Learning Approach
Hit paper breakdown →
2015361
2 201175
3 201067
4 202063
5 201344
6 201942
7 200841
8 201333
9 201429
10 201528
11 201321
12 201721
13 201120
14 201620
15 201917
16 201616
17 200714
18 200912
19 201511
20 201610

About Hani Mowafi

Hani Mowafi is a scholar working on Emergency Medical Services, Emergency Medicine, General Health Professions, Public Health, Environmental and Occupational Health and Clinical Psychology, having authored 46 papers that have together received 1.0k indexed citations. Recurring topics across this work include Disaster Response and Management (10 papers), Emergency and Acute Care Studies (6 papers), Trauma and Emergency Care Studies (6 papers), Health and Conflict Studies (5 papers), Global Health Workforce Issues (3 papers), Global Health and Surgery (2 papers), Global Maternal and Child Health (2 papers) and Injury Epidemiology and Prevention (2 papers). The work is most often cited by research in Health Informatics (30 citations), Emergency Medical Services (130 citations), Emergency Medicine (161 citations), Family Practice (19 citations) and Health Information Management (45 citations). Hani Mowafi has collaborated with scholars based in United States, Lebanon and Uganda. Frequent co-authors include Edward R. Melnick, M. Kennedy Hall, Richard A. Taylor, Arjun K. Venkatesh, William Fleischman, Joseph R. Pare, Paul Spiegel, Ali Ardalan, Michael J. VanRooyen and Monir Mazaheri. Their work appears in journals such as Prehospital and Disaster Medicine, Academic Emergency Medicine, Journal of Emergency Medicine, BMJ Global Health and Injury.

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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