Fida K. Dankar

1.7k citations
31 papers · 1.0k indexed · h-index 16

Impact in

Papers in

Fida K. Dankar

30 papers receiving 962 citations

Peers

Fida K. Dankar
Comparison fields: 5 of 104
  • Health Informatics 79
  • Artificial Intelligence 688
  • Computer Science Applications 61
  • Management Science and Operations Research 128
  • Public Health, Environmental and Occupational Health 281
Replace Fabian Praßer with:
Fabian Praßer Germany
Grigorios Loukides United Kingdom
Elizabeth Jonker Canada
Vijay Mago Canada
Franck Dernoncourt United States
Jean Louis Raisaro Switzerland
Luca Bonomi United States
Luc Rocher United Kingdom
Guido Zuccon Australia
Juan Ramón Troncoso-Pastoriza Spain
Fida K. Dankar relative to Fabian Praßer Germany Fabian Praßer's profile →
Citations per field
00.5×1.5×1.9×
Fabian Praßer · 1×
Citations per year

Countries citing papers authored by Fida K. Dankar

Since Specialization
Citations

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

Fields of papers citing papers by Fida K. Dankar

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Fida K. Dankar. 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 Fida K. Dankar. The network helps show where Fida K. Dankar may publish in the future.

Co-authors

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

All Works

20 of 20 papers shown
#Work
1 20253
2 20253
3 20245
4 20212
5 202163
6 202042
7 20203
8 201917
9 201940
10 201715
11
Using Robust Estimation Theory to Design Efficient Secure Multiparty Linear Regression.
20162
12 201512
13
Secure Multi-Party linear Regression
20145
14 201320
15 201215
16 201262
17 201123
18 201025
19 200944
20 2009153

About Fida K. Dankar

Fida K. Dankar is a scholar working on Health Informatics, Artificial Intelligence, Public Health, Environmental and Occupational Health, Management Science and Operations Research and Statistics and Probability, having authored 31 papers that have together received 1.0k indexed citations. Recurring topics across this work include Privacy-Preserving Technologies in Data (21 papers), Ethics in Clinical Research (11 papers), Cryptography and Data Security (7 papers), Privacy, Security, and Data Protection (6 papers), Healthcare Policy and Management (4 papers), Patient Dignity and Privacy (4 papers), Data Quality and Management (4 papers) and Artificial Intelligence in Healthcare and Education (3 papers). The work is most often cited by research in Health Informatics (79 citations), Artificial Intelligence (688 citations), Computer Science Applications (61 citations), Management Science and Operations Research (128 citations) and Public Health, Environmental and Occupational Health (281 citations). Fida K. Dankar has collaborated with scholars based in Canada, United Arab Emirates and Qatar. Frequent co-authors include Khaled El Emam, Tyson Roffey, Samar Dankar, Régis Vaillancourt, Angelica Neisa, Elizabeth Jonker, Leila Ismail, Radja Badji, Elise Cogo and Jean‐Pierre Corriveau. Their work appears in journals such as Computational and Structural Biotechnology Journal, BMC Medical Informatics and Decision Making, IEEE Access, Journal of the American Medical Informatics Association and Human Genomics.

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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