Mehdi Naseriparsa

844 citations
13 papers · 413 indexed · 1 hit paper · h-index 8
Topics
Artificial Intelligence in Healthcare (3 papers)Advanced Database Systems and Queries (3 papers)Advanced Graph Neural Networks (3 papers)
Partner nations
AustraliaChinaIran

In The Last Decade

Mehdi Naseriparsa

13 papers receiving 394 citations

Hit Papers

Knowledge Graphs: Opportunities and Challenges2023202620242025202350100150200

Peers

Mehdi Naseriparsa
Comparison fields: 5 of 95
  • Artificial Intelligence 266
  • Information Systems 76
  • Management Science and Operations Research 41
  • Computer Vision and Pattern Recognition 39
  • Molecular Biology 32
Replace Jalel Akaichi with:
Jalel Akaichi Tunisia
Linhao Luo Australia
Iván López-Arévalo Mexico
Jiapu Wang China
S. Balamurugan India
Yogan Jaya Kumar Malaysia
Sujala D. Shetty United Arab Emirates
Raji Ghawi Germany
Yuyu Yuan China
Mehdi Naseriparsa relative to Jalel Akaichi Tunisia Jalel Akaichi's profile →
Citations per field
00.5×10×13.8×
Jalel Akaichi · 1×
Citations per year

Countries citing papers authored by Mehdi Naseriparsa

Since Specialization
Citations

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

Fields of papers citing papers by Mehdi Naseriparsa

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Mehdi Naseriparsa

This figure shows the co-authorship network connecting the top 25 collaborators of Mehdi Naseriparsa. A scholar is included among the top collaborators of Mehdi Naseriparsa 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 Mehdi Naseriparsa. Mehdi Naseriparsa is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

13 of 13 papers shown
#WorkIndexed citations
1
Knowledge Graphs: Opportunities and Challengesbreakdown →
219
2 17
3 10
4 4
5 30
6 2
7 28
8 23
9 1
10 4
11 5
12 40
13 30

About Mehdi Naseriparsa

Mehdi Naseriparsa is a scholar working on Health Information Management, Signal Processing and Artificial Intelligence, having authored 13 papers that have together received 413 indexed citations. Recurring topics across this work include Artificial Intelligence in Healthcare (3 papers), Advanced Database Systems and Queries (3 papers) and Advanced Graph Neural Networks (3 papers). The work is most often cited by research in Artificial Intelligence (266 citations), Health Information Management (32 citations) and Information Systems (76 citations). Mehdi Naseriparsa has collaborated with scholars based in Australia, China and Iran. Frequent co-authors include Feng Xia, Francesco Osborne, Ciyuan Peng, Rui Zhou, Chengfei Liu, Ming Sheng, Shuo Yu, Yong Zhang, Zhehuan Zhao and Bo Xu. Their work appears in journals such as Artificial Intelligence Review, International Journal of Medical Informatics and Data & Knowledge Engineering.

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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