Longxin Lin

400 citations
10 papers · 283 · h-index 5

Impact in

Papers in

Longxin Lin

9 papers receiving 261 citations

Peers

Longxin Lin
Comparison fields: 5 of 85
  • Health Information Management 20
  • Artificial Intelligence 101
  • Health Informatics 4
  • Information Systems 63
  • Computer Networks and Communications 43
Replace Anurag Sharma with:
Anurag Sharma Fiji
Harsurinder Kaur India
Purvi Prajapati India
Dost Muhammad Khan Pakistan
Roheet Bhatnagar India
Essam Al Daoud Jordan
Martin Pawelczyk Germany
Mamoon M. Saeed Yemen
Roy Wedge United States
Longxin Lin relative to Anurag Sharma Fiji Anurag Sharma's profile →
Citations per field
00.5×5.3×
Anurag Sharma · 1×
Citations per year

Countries citing papers authored by Longxin Lin

Since Specialization
Citations

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

Fields of papers citing papers by Longxin Lin

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 10 scholars most cited alongside Longxin Lin, 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 Longxin Lin Line = papers co-authored together Longxin Lin links everyone, so they are left out of the graph.

All Works

10 of 10 papers shown
#Work
1 2017225
2 201732
3 20158
4 20205
5 20165
6 20193
7
the Empirical Research on the Stimulative Effect of Foreign Direct Investment in China on its Service Export Based on the Gravity Model
20122
8 20251
9 20141
10 20111

About Longxin Lin

Longxin Lin is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Information Systems, Computer Networks and Communications and General Health Professions, having authored 10 papers that have together received 283 indexed citations. Recurring topics across this work include Imbalanced Data Classification Techniques (2 papers), Data Mining Algorithms and Applications (2 papers), Advanced Image and Video Retrieval Techniques (2 papers), Anomaly Detection Techniques and Applications (2 papers), Global Health Care Issues (1 paper), Regional Economic and Spatial Analysis (1 paper), Cryptography and Data Security (1 paper) and Global Healthcare and Medical Tourism (1 paper). The work is most often cited by research in Health Information Management (20 citations), Artificial Intelligence (101 citations), Health Informatics (4 citations), Information Systems (63 citations) and Computer Networks and Communications (43 citations). Longxin Lin has collaborated with scholars based in China, United States and United Kingdom. Frequent co-authors include Weiwei Lin, Ziming Wu, Jin Li, Zilong Zhang, Weijun Xiao, Cheng Chen, Rui Gu, Xiaoxin Li, Quan Qi and Yongqiang Cheng. Their work appears in journals such as Soft Computing, IEEE Access, Mathematical Problems in Engineering and Sunderland Repository (University of Sunderland).

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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