Lise Wei

1.4k citations
24 papers · 860 · 1 hit paper · h-index 13

Impact in

Papers in

Lise Wei

24 papers receiving 842 citations

Lise Wei's Hit Papers

Machine and deep learning methods for radiomics 2020 · 360 citations
3600+2+4Years since publication100200300

Peers

Lise Wei
Comparison fields: 5 of 100
  • Health Informatics 78
  • Radiology, Nuclear Medicine and Imaging 627
  • Hepatology 67
  • Pulmonary and Respiratory Medicine 218
  • Radiation 53
Replace Kyle J. Lafata with:
Kyle J. Lafata United States
Turkey Refaee Saudi Arabia
Aydın Demircioğlu Germany
Maria Vakalopoulou France
Roman Zeleznik United States
Ghasem Hajianfar Iran
Stefano Trebeschi Netherlands
Fadila Zerka Netherlands
Qingxia Wu China
Steve Bandula United Kingdom
Lise Wei relative to Kyle J. Lafata United States Kyle J. Lafata's profile →
Citations per field
00.5×1.5×
Kyle J. Lafata · 1×
Citations per year

Countries citing papers authored by Lise Wei

Since Specialization
Citations

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

Fields of papers citing papers by Lise Wei

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 24 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Machine and deep learning methods for radiomics
Hit paper breakdown →
2020360
2 201977
3 202163
4 202363
5 201846
6 202142
7 201936
8 201725
9 200321
10 201919
11 202016
12 202215
13 202014
14 201511
15 20239
16 20239
17 19889
18 20228
19 20245
20 20035

About Lise Wei

Lise Wei is a scholar working on Radiology, Nuclear Medicine and Imaging, Artificial Intelligence, Biomedical Engineering, Hepatology and Pulmonary and Respiratory Medicine, having authored 24 papers that have together received 860 indexed citations. Recurring topics across this work include Radiomics and Machine Learning in Medical Imaging (18 papers), Advanced X-ray and CT Imaging (6 papers), Hepatocellular Carcinoma Treatment and Prognosis (5 papers), AI in cancer detection (5 papers), Medical Imaging Techniques and Applications (4 papers), MRI in cancer diagnosis (3 papers), Advanced Radiotherapy Techniques (2 papers) and Lung Cancer Diagnosis and Treatment (2 papers). The work is most often cited by research in Health Informatics (78 citations), Radiology, Nuclear Medicine and Imaging (627 citations), Hepatology (67 citations), Pulmonary and Respiratory Medicine (218 citations) and Radiation (53 citations). Lise Wei has collaborated with scholars based in United States, France and Netherlands. Frequent co-authors include Issam El Naqa, Martin Vallières, Michele Avanzo, Joseph Stancanello, Sarah A. Mattonen, Olivier Morin, Arvind Rao, Sunan Cui, Randall K. Ten Haken and Yi Luo. Their work appears in journals such as International Journal of Radiation Oncology*Biology*Physics, British Journal of Radiology, Medical Physics, Physics and Imaging in Radiation Oncology and EJNMMI 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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