Farimah Hadjilooei

762 citations
15 papers · 496 indexed · 1 hit paper · h-index 7
Topics
COVID-19 and healthcare impacts (5 papers)COVID-19 diagnosis using AI (4 papers)COVID-19 epidemiological studies (3 papers)
Journals
SHILAP Revista de lepidopterologíaIEEE AccessCancer Immunology Immunotherapy

In The Last Decade

Farimah Hadjilooei

15 papers receiving 481 citations

Hit Papers

Artificial Intelligence and COVID-19: Deep Learning Appro...20202026202220242020100200300

Peers

Farimah Hadjilooei
Comparison fields: 5 of 103
  • Radiology, Nuclear Medicine and Imaging 259
  • Artificial Intelligence 170
  • Oncology 63
  • Health Informatics 57
  • Health Information Management 49
Replace Alireza Jamshidi with:
Alireza Jamshidi Iran
Yazeed Zoabi Israel
Holly Wiberg United States
Pedram Lalbakhsh Iran
Cathal McCague United Kingdom
Mubarak Taiwo Mustapha Cyprus
Meiyu Duan China
P Swetha India
Abolfazl Zargari Khuzani United States
Zhongxiao Li Saudi Arabia
Farimah Hadjilooei relative to Alireza Jamshidi Iran Alireza Jamshidi's profile →
Citations per field
00.5×10.5×
Alireza Jamshidi · 1×
Citations per year

Countries citing papers authored by Farimah Hadjilooei

Since Specialization
Citations

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

Fields of papers citing papers by Farimah Hadjilooei

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Farimah Hadjilooei

This figure shows the co-authorship network connecting the top 25 collaborators of Farimah Hadjilooei. A scholar is included among the top collaborators of Farimah Hadjilooei based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Farimah Hadjilooei. Farimah Hadjilooei is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

15 of 15 papers shown
#WorkIndexed citations
1 2
2 1
3 1
4 18
5 20
6 2
7 7
8 34
9 2
10 3
11 2
12 1
13 10
14
Artificial Intelligence and COVID-19: Deep Learning Approaches for Diagnosis and Treatmentbreakdown →
369
15 24

About Farimah Hadjilooei

Farimah Hadjilooei is a scholar working on Modeling and Simulation, Oncology and Radiology, Nuclear Medicine and Imaging, having authored 15 papers that have together received 496 indexed citations. Recurring topics across this work include COVID-19 and healthcare impacts (5 papers), COVID-19 diagnosis using AI (4 papers) and COVID-19 epidemiological studies (3 papers). The work is most often cited by research in Health Informatics (57 citations), Radiology, Nuclear Medicine and Imaging (259 citations) and Modeling and Simulation (49 citations). Farimah Hadjilooei has collaborated with scholars based in Iran, United States and Australia. Frequent co-authors include Jakub Talla, Pedram Lalbakhsh, Zdeněk Peroutka, Ali Lalbakhsh, Mohammad Jamshidi, Sobhan Roshani, Saeed Roshani, Alireza Jamshidi, Bahare Mohamadzade and Sara Kiani. Their work appears in journals such as SHILAP Revista de lepidopterología, IEEE Access and Cancer Immunology Immunotherapy.

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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