Kun Lan

602 citations
31 papers · 373 · h-index 10

Impact in

Papers in

Kun Lan

26 papers receiving 361 citations

Peers

Kun Lan
Comparison fields: 5 of 110
  • Health Informatics 7
  • Health Information Management 22
  • Ecological Modeling 17
  • Artificial Intelligence 117
  • Radiology, Nuclear Medicine and Imaging 77
Replace Suzana Loškovska with:
Suzana Loškovska North Macedonia
Tina Babu India
Ghadah Naif Alwakid Saudi Arabia
Ivica Dimitrovski North Macedonia
Prabhpreet Kaur India
Carl Sabottke United States
Serkan Savaş Türkiye
Shailender Kumar India
Agung W. Setiawan Indonesia
Md. Abul Ala Walid Bangladesh
Kun Lan relative to Suzana Loškovska North Macedonia Suzana Loškovska's profile →
Citations per field
00.5×5.7×
Suzana Loškovska · 1×
Citations per year

Countries citing papers authored by Kun Lan

Since Specialization
Citations

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

Fields of papers citing papers by Kun Lan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 31 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2018190
2 202123
3 202420
4 202417
5 202016
6 202312
7 202211
8 201710
9 202210
10 20199
11 20217
12 20246
13 20225
14 20225
15 20205
16 20224
17 20224
18 20234
19 20233
20 20232

About Kun Lan

Kun Lan is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Radiology, Nuclear Medicine and Imaging, Neurology and Molecular Biology, having authored 31 papers that have together received 373 indexed citations. Recurring topics across this work include AI in cancer detection (5 papers), Advanced Neural Network Applications (3 papers), Brain Tumor Detection and Classification (3 papers), Advanced Image and Video Retrieval Techniques (3 papers), COVID-19 diagnosis using AI (2 papers), Time Series Analysis and Forecasting (2 papers), Metaheuristic Optimization Algorithms Research (2 papers) and Imbalanced Data Classification Techniques (2 papers). The work is most often cited by research in Health Informatics (7 citations), Health Information Management (22 citations), Ecological Modeling (17 citations), Artificial Intelligence (117 citations) and Radiology, Nuclear Medicine and Imaging (77 citations). Kun Lan has collaborated with scholars based in China, Macao and Australia. Frequent co-authors include Simon Fong, Kelvin K. L. Wong, Nilanjan Dey, Dantong Wang, Liansheng Liu, Xiaoliang Jiang, Jie Yang, Rui Tang, Raymond K. Wong and Liansheng Liu. Their work appears in journals such as Mathematical Biosciences & Engineering, Enterprise Information Systems, Scientific Reports, IEEE Geoscience and Remote Sensing Letters and Journal of Medical Systems.

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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