Nabil Alshurafa

90 papers receiving 1.8k citations

Peers

Nabil Alshurafa
Comparison fields: 5 of 130
  • Human-Computer Interaction 206
  • Applied Psychology 175
  • Family Practice 70
  • Computer Vision and Pattern Recognition 601
  • Health Information Management 81
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Haik Kalantarian United States
Holly Jimison United States
Ilkka Korhonen Finland
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Mark W. Scerbo United States
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Citations per field
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Haik Kalantarian · 1×
Citations per year

Countries citing papers authored by Nabil Alshurafa

Since Specialization
Citations

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

Fields of papers citing papers by Nabil Alshurafa

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 97 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2015119
2 2017114
3 201386
4 202078
5 201373
6 201572
7 202069
8 201365
9 201464
10 201752
11 201650
12 201250
13 201649
14 201646
15 201446
16 201743
17 201442
18 201539
19 201537
20 201835

About Nabil Alshurafa

Nabil Alshurafa is a scholar working on Computer Vision and Pattern Recognition, General Health Professions, Biomedical Engineering, Public Health, Environmental and Occupational Health and Physiology, having authored 97 papers that have together received 1.9k indexed citations. Recurring topics across this work include Context-Aware Activity Recognition Systems (27 papers), Mobile Health and mHealth Applications (26 papers), Nutritional Studies and Diet (14 papers), Digital Mental Health Interventions (11 papers), Non-Invasive Vital Sign Monitoring (9 papers), Innovative Human-Technology Interaction (9 papers), Obesity, Physical Activity, Diet (8 papers) and Advanced Sensor and Energy Harvesting Materials (8 papers). The work is most often cited by research in Human-Computer Interaction (206 citations), Applied Psychology (175 citations), Family Practice (70 citations), Computer Vision and Pattern Recognition (601 citations) and Health Information Management (81 citations). Nabil Alshurafa has collaborated with scholars based in United States, India and Philippines. Frequent co-authors include Majid Sarrafzadeh, Haik Kalantarian, Wenyao Xu, Mohammad Pourhomayoun, Jason J. Liu, Ming-Chun Huang, Tuan Le, Bobak J. Mortazavi, Feng Lin and Shibo Zhang. Their work appears in journals such as IEEE Journal of Biomedical and Health Informatics, Proceedings of the ACM on Interactive Mobile Wearable and Ubiquitous Technologies, npj Digital Medicine, IEEE Sensors Journal and Journal of Medical Internet 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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