Daniel Najafali

798 citations
50 papers · 487 · h-index 9

Impact in

Papers in

    • Reconstructive Surgery and Microvascular Techniques 4
    • Artificial Intelligence in Healthcare and Education 8

Daniel Najafali

37 papers receiving 482 citations

Peers

Daniel Najafali
Comparison fields: 5 of 92
  • Health Informatics 57
  • Biomaterials 50
  • Biomedical Engineering 163
  • Cancer Research 50
  • Genetics 24
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Citations per field
00.5×10×14.3×
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Citations per year

Countries citing papers authored by Daniel Najafali

Since Specialization
Citations

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

Fields of papers citing papers by Daniel Najafali

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 50 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2020257
2 201931
3 202330
4 202225
5 202324
6 201815
7 202110
8 20218
9 20248
10 20237
11 20236
12 20226
13 20226
14 20216
15 20235
16
Addressing the Rhino in the Room: ChatGPT Creates "Novel" Patent Ideas for Rhinoplasty.
20244
17 20223
18 20253
19 20243
20 20203

About Daniel Najafali

Daniel Najafali is a scholar working on Surgery, Health Informatics, Epidemiology, Public Health, Environmental and Occupational Health and Pulmonary and Respiratory Medicine, having authored 50 papers that have together received 487 indexed citations. Recurring topics across this work include Artificial Intelligence in Healthcare and Education (8 papers), Diversity and Career in Medicine (4 papers), Reconstructive Surgery and Microvascular Techniques (4 papers), Photodynamic Therapy Research Studies (3 papers), Lymphatic System and Diseases (3 papers), Intracerebral and Subarachnoid Hemorrhage Research (3 papers), Burn Injury Management and Outcomes (3 papers) and Spinal Cord Injury Research (2 papers). The work is most often cited by research in Health Informatics (57 citations), Biomaterials (50 citations), Biomedical Engineering (163 citations), Cancer Research (50 citations) and Genetics (24 citations). Daniel Najafali has collaborated with scholars based in United States, Germany and Canada. Frequent co-authors include Huang‐Chiao Huang, Michael Pigula, Yan Baglo, Barry J. Liang, Tayyaba Hasan, Shane D. Morrison, Amir H. Dorafshar, Quincy Tran, Graeme F. Woodworth and Collin T. Inglut. Their work appears in journals such as Journal of Burn Care & Research, The American Journal of Emergency Medicine, Aesthetic Surgery Journal, Annals of Plastic Surgery and Journal of Surgical Oncology.

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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