Hani Mowafi

1.5k citations
44 papers · 966 · 1 hit paper · h-index 15

Impact in

Papers in

Hani Mowafi

42 papers receiving 947 citations

Hit Papers

Prediction of In‐hospital Mortality in Emergency Department Patients With Sepsis: A Local Big Data–Driven, Machine Learning Approach 2015 · 336 citations
3360+3+7Years since publication100200300

Peers

Hani Mowafi
Comparison fields: 5 of 121
  • Emergency Medical Services 198
  • Emergency Medicine 256
  • Health Informatics 34
  • Family Practice 33
  • Health Information Management 63
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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 44 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 →
2015336
2 201164
3 201062
4 202061
5 201344
6 200839
7 201938
8 201332
9 201428
10 201527
11 201721
12 201320
13 201119
14 201619
15 201914
16 200714
17 201613
18 200912
19 201511
20 20209

About Hani Mowafi

Hani Mowafi is a scholar working on Emergency Medicine, Emergency Medical Services, Public Health, Environmental and Occupational Health, General Health Professions and Clinical Psychology, having authored 44 papers that have together received 966 indexed citations. Recurring topics across this work include Disaster Response and Management (14 papers), Trauma and Emergency Care Studies (13 papers), Emergency and Acute Care Studies (11 papers), Global Health Workforce Issues (5 papers), Health and Conflict Studies (5 papers), Injury Epidemiology and Prevention (5 papers), Migration, Health and Trauma (4 papers) and Occupational Health and Safety Research (3 papers). The work is most often cited by research in Emergency Medical Services (198 citations), Emergency Medicine (256 citations), Health Informatics (34 citations), Family Practice (33 citations) and Health Information Management (63 citations). Hani Mowafi has collaborated with scholars based in United States, Lebanon and Uganda. Frequent co-authors include Arjun K. Venkatesh, Joseph R. Pare, William Fleischman, Richard A. Taylor, Edward R. Melnick, M. Kennedy Hall, Paul Spiegel, Ali Ardalan, Michael J. VanRooyen and Monir Mazaheri. Their work appears in journals such as Prehospital and Disaster Medicine, Academic Emergency Medicine, BMJ Global Health, Injury and Journal of Emergency Medicine.

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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