Farnoosh Naderkhani

981 citations
45 papers · 573 indexed · h-index 14

Farnoosh Naderkhani

42 papers receiving 554 citations

Peers

Farnoosh Naderkhani
Comparison fields: 5 of 93
  • Health Informatics 33
  • Medical Laboratory Technology 17
  • Safety, Risk, Reliability and Quality 97
  • Statistics, Probability and Uncertainty 71
  • Radiology, Nuclear Medicine and Imaging 202
Replace Zeina Al Masry with:
Zeina Al Masry France
Jianwei Chen China
Karan Aggarwal India
Wan-Jui Lee Taiwan
Felician Campean United Kingdom
Rahul K. Sevakula India
Mohamed K. Nour Saudi Arabia
Xiwang He China
Tarek Berghout Algeria
Farnoosh Naderkhani relative to Zeina Al Masry France Zeina Al Masry's profile →
Citations per field
00.5×4.7×
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Citations per year

Countries citing papers authored by Farnoosh Naderkhani

Since Specialization
Citations

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

Fields of papers citing papers by Farnoosh Naderkhani

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

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

All Works

20 of 20 papers shown
#Work
1 20251
2 20243
3 20241
4 20244
5 20241
6 202311
7 20231
8 202336
9 20231
10 20231
11 20230
12 202213
13 202220
14 20223
15 2021134
16 202118
17 202039
18 202018
19 201628
20 20151

About Farnoosh Naderkhani

Farnoosh Naderkhani is a scholar working on Medical Laboratory Technology, Safety, Risk, Reliability and Quality and Software, having authored 45 papers that have together received 573 indexed citations. Recurring topics across this work include Reliability and Maintenance Optimization (15 papers), COVID-19 diagnosis using AI (9 papers), Radiomics and Machine Learning in Medical Imaging (8 papers), Advanced Statistical Process Monitoring (8 papers), Software Reliability and Analysis Research (6 papers), Machine Fault Diagnosis Techniques (6 papers), Lung Cancer Diagnosis and Treatment (5 papers) and Quality and Safety in Healthcare (4 papers). The work is most often cited by research in Health Informatics (33 citations), Medical Laboratory Technology (17 citations) and Safety, Risk, Reliability and Quality (97 citations). Farnoosh Naderkhani has collaborated with scholars based in Canada, Iran and United States. Frequent co-authors include Arash Mohammadi, Nastaran Enshaei, Viliam Makiš, Anastasia Oikonomou, Parnian Afshar, Konstantinos N. Plataniotis, Shahin Heidarian, Moezedin Javad Rafiee, Elahe Rahimian and Svetlana Yanushkevich. Their work appears in journals such as PLoS ONE, Scientific Reports and Expert Systems with Applications.

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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