Lin Lü

4.0k citations
105 papers · 2.9k · 1 hit paper · h-index 29

Impact in

Papers in

Lin Lü

100 papers receiving 2.9k citations

Hit Papers

Reproducibility of radiomics for deciphering tumor phenotype with imaging 2016 · 412 citations
4120+3+6Years since publication100200300400

Peers

Lin Lü
Comparison fields: 5 of 141
  • Radiology, Nuclear Medicine and Imaging 1.8k
  • Health Informatics 61
  • Pulmonary and Respiratory Medicine 840
  • Hepatology 191
  • Oncology 476
Replace Yuan Ji with:
Yuan Ji United States
Ruijiang Li United States
M.M. Matuszak United States
Cary Oberije Netherlands
Johan van Soest Netherlands
Ying Xiao United States
Jongphil Kim United States
Erich P. Huang United States
Thomas G. Purdie Canada
Insuk Sohn South Korea
Lin Lü relative to Yuan Ji United States Yuan Ji's profile →
Citations per field
00.5×1.5×2.4×
Yuan Ji · 1×
Citations per year

Countries citing papers authored by Lin Lü

Since Specialization
Citations

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

Fields of papers citing papers by Lin Lü

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 105 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Reproducibility of radiomics for deciphering tumor phenotype with imaging
Hit paper breakdown →
2016412
2 2018173
3 2019136
4 2020128
5 2016127
6 2020113
7 2014105
8 201696
9 201870
10 201867
11 201867
12 202066
13 202163
14 202257
15 201555
16 201952
17 201850
18 201747
19 201944
20 201939

About Lin Lü

Lin Lü is a scholar working on Radiology, Nuclear Medicine and Imaging, Molecular Biology, Oncology, Pulmonary and Respiratory Medicine and Biomedical Engineering, having authored 105 papers that have together received 2.9k indexed citations. Recurring topics across this work include Radiomics and Machine Learning in Medical Imaging (34 papers), Advanced X-ray and CT Imaging (17 papers), Machine Learning in Bioinformatics (17 papers), Lung Cancer Diagnosis and Treatment (14 papers), Colorectal Cancer Screening and Detection (11 papers), AI in cancer detection (10 papers), Cardiac Imaging and Diagnostics (8 papers) and Medical Image Segmentation Techniques (7 papers). The work is most often cited by research in Radiology, Nuclear Medicine and Imaging (1.8k citations), Health Informatics (61 citations), Pulmonary and Respiratory Medicine (840 citations), Hepatology (191 citations) and Oncology (476 citations). Lin Lü has collaborated with scholars based in China, United States and France. Frequent co-authors include Binsheng Zhao, Lawrence H. Schwartz, Yongqiang Tan, Yu‐Dong Cai, Laurent Dercle, Chuanmiao Xie, Wei‐Yann Tsai, Jing Qi, Fadel M. Megahed and Lei Chen. Their work appears in journals such as European Radiology, Molecular Diversity, Journal of Cardiovascular Magnetic Resonance, Tomography and American Journal of Roentgenology.

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.

Explore authors with similar magnitude of impact