Leonard Wee

4.4k citations
127 papers · 2.5k · 1 hit paper · h-index 25

Impact in

Papers in

Leonard Wee

113 papers receiving 2.5k citations

Leonard Wee's Hit Papers

Repeatability and Reproducibility of Radiomic Features: A Systematic Review 2018 · 588 citations
5880+2+5Years since publication100200300400500

Peers

Leonard Wee
Comparison fields: 5 of 128
  • Health Informatics 182
  • Radiology, Nuclear Medicine and Imaging 1.9k
  • Radiation 259
  • Pulmonary and Respiratory Medicine 695
  • Otorhinolaryngology 77
Replace Kujtim Latifi with:
Kujtim Latifi United States
MingDe Lin United States
Isaac Shiri Switzerland
George C. Kagadis Greece
Michael Ingrisch Germany
Jiazhou Wang China
Benjamin H. Kann United States
Jurgen J. Fütterer Netherlands
Thibaud Coroller United States
Tianye Niu China
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Citations per field
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Citations per year

Countries citing papers authored by Leonard Wee

Since Specialization
Citations

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

Fields of papers citing papers by Leonard Wee

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 127 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Repeatability and Reproducibility of Radiomic Features: A Systematic Review
Hit paper breakdown →
2018588
2 2018220
3 202074
4 202173
5 201664
6 201964
7 202163
8 201955
9 202253
10 199952
11 202050
12 201948
13 201845
14 201943
15 201941
16 202041
17 201437
18 202132
19 202329
20 200429

About Leonard Wee

Leonard Wee is a scholar working on Radiology, Nuclear Medicine and Imaging, Pulmonary and Respiratory Medicine, Biomedical Engineering, Artificial Intelligence and Oncology, having authored 127 papers that have together received 2.5k indexed citations. Recurring topics across this work include Radiomics and Machine Learning in Medical Imaging (74 papers), Advanced X-ray and CT Imaging (28 papers), Lung Cancer Diagnosis and Treatment (28 papers), AI in cancer detection (21 papers), Medical Imaging Techniques and Applications (16 papers), Advanced Radiotherapy Techniques (15 papers), Magnetic properties of thin films (11 papers) and Magnetic Properties and Applications (11 papers). The work is most often cited by research in Health Informatics (182 citations), Radiology, Nuclear Medicine and Imaging (1.9k citations), Radiation (259 citations), Pulmonary and Respiratory Medicine (695 citations) and Otorhinolaryngology (77 citations). Leonard Wee has collaborated with scholars based in Netherlands, Australia and United States. Frequent co-authors include André Dekker, Alberto Traverso, Robert J. Gillies, David A. Jaffray, Zhenwei Shi, Mattea Welch, Iñigo Bermejo, R. L. Stamps, Ivan Zhovannik and Juha Korhonen. Their work appears in journals such as Radiotherapy and Oncology, Medical Physics, Physica Medica, Scientific Reports and Journal of Applied Physics.

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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