Lan Li

54 papers receiving 730 citations

Peers

Lan Li
Comparison fields: 5 of 109
  • Artificial Intelligence 479
  • Radiology, Nuclear Medicine and Imaging 342
  • Pulmonary and Respiratory Medicine 248
  • Health Informatics 9
  • Computer Vision and Pattern Recognition 119
Replace Ehsan Kazemi with:
Ehsan Kazemi United States
Mohamed Roushdy Egypt
Konstantin Pogorelov Norway
Xuechen Li China
Changhee Han South Korea
Cheng Zhong China
Xun Zhao China
Omar S. Al-Kadi Jordan
Dhairya Vyas India
Wenting Tu China
Lan Li relative to Ehsan Kazemi United States Ehsan Kazemi's profile →
Citations per field
00.5×3.2×
Ehsan Kazemi · 1×
Citations per year

Countries citing papers authored by Lan Li

Since Specialization
Citations

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

Fields of papers citing papers by Lan Li

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 61 papers — load more, or switch the sort, to bring in the rest.

#Work
1 200485
2 200776
3 200574
4 200672
5 200552
6 201451
7 202151
8 201235
9 200230
10 200825
11 201422
12 201422
13 200322
14 200416
15 199213
16 200810
17 202310
18 20248
19 20227
20 20236

About Lan Li

Lan Li is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Radiology, Nuclear Medicine and Imaging, Pulmonary and Respiratory Medicine and Media Technology, having authored 61 papers that have together received 762 indexed citations. Recurring topics across this work include AI in cancer detection (20 papers), Radiomics and Machine Learning in Medical Imaging (12 papers), Digital Radiography and Breast Imaging (10 papers), Advanced Image Fusion Techniques (6 papers), Image and Signal Denoising Methods (5 papers), Gene expression and cancer classification (5 papers), Remote Sensing and Land Use (4 papers) and Image Enhancement Techniques (4 papers). The work is most often cited by research in Artificial Intelligence (479 citations), Radiology, Nuclear Medicine and Imaging (342 citations), Pulmonary and Respiratory Medicine (248 citations), Health Informatics (9 citations) and Computer Vision and Pattern Recognition (119 citations). Lan Li has collaborated with scholars based in China, United States and Canada. Frequent co-authors include Maryellen L. Giger, Hui Li, Olufunmilayo I. Olopade, Gyungho Lee, Karla Horsch, Carl J. Vyborny, Zhimin Huo, Min Kyung Lee, R. Edward Hendrick and Barbara Weber. Their work appears in journals such as Medical Physics, Academic Radiology, IEEE Transactions on Geoscience and Remote Sensing, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing and Breast Cancer Research.

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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