Luyi Han

622 citations
22 papers · 284 · h-index 8

Impact in

Papers in

Luyi Han

19 papers receiving 279 citations

Peers

Luyi Han
Comparison fields: 5 of 50
  • Health Informatics 25
  • Radiology, Nuclear Medicine and Imaging 192
  • Artificial Intelligence 187
  • Computer Vision and Pattern Recognition 76
  • Neurology 23
Replace Ehab A. AlBadawy with:
Ehab A. AlBadawy United States
Firas Khader Germany
Nikos Tsiknakis Greece
Eleftherios Trivizakis Greece
Yan‐Wei Lee Taiwan
Khushboo Munir Italy
Richard Osuala Spain
Mehmet Ufuk Dalmış Netherlands
Alessia Angela Maria Orlando Italy
Luyi Han relative to Ehab A. AlBadawy United States Ehab A. AlBadawy's profile →
Citations per field
00.5×2.8×
Ehab A. AlBadawy · 1×
Citations per year

Countries citing papers authored by Luyi Han

Since Specialization
Citations

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

Fields of papers citing papers by Luyi Han

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 22 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201975
2 201955
3 202337
4 202224
5 202424
6 202320
7 202214
8 20239
9 20236
10 20256
11 20245
12 20222
13 20251
14 20231
15 20251
16 20251
17 20251
18 20241
19 20221
20 20250

About Luyi Han

Luyi Han is a scholar working on Radiology, Nuclear Medicine and Imaging, Artificial Intelligence, Computer Vision and Pattern Recognition, Cancer Research and Neurology, having authored 22 papers that have together received 284 indexed citations. Recurring topics across this work include AI in cancer detection (12 papers), Radiomics and Machine Learning in Medical Imaging (12 papers), Medical Image Segmentation Techniques (5 papers), Breast Cancer Treatment Studies (3 papers), MRI in cancer diagnosis (3 papers), Brain Tumor Detection and Classification (3 papers), Medical Imaging Techniques and Applications (2 papers) and Textile materials and evaluations (2 papers). The work is most often cited by research in Health Informatics (25 citations), Radiology, Nuclear Medicine and Imaging (192 citations), Artificial Intelligence (187 citations), Computer Vision and Pattern Recognition (76 citations) and Neurology (23 citations). Luyi Han has collaborated with scholars based in Netherlands, China and United States. Frequent co-authors include Yunzhi Huang, Haoran Dou, Qi Liu, Honghao Luo, Ritse M. Mann, Tao Tan, Jiang Zhang, Tianyu Zhang, Jingfan Fan and Shuai Wang. Their work appears in journals such as IEEE Journal of Biomedical and Health Informatics, Computer Methods and Programs in Biomedicine, Pattern Recognition, Textile Research Journal and npj Breast Cancer.

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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