Feyisope Eweje

648 citations
9 papers · 239 indexed · 1 hit paper · h-index 6
Topics
Radiomics and Machine Learning in Medical Imaging (6 papers)AI in cancer detection (3 papers)Medical Imaging and Pathology Studies (2 papers)
Partner nations
United StatesChina

In The Last Decade

Feyisope Eweje

7 papers receiving 232 citations

Hit Papers

A vision–language foundation model for precision oncology20252026202510203040

Peers

Feyisope Eweje
Comparison fields: 5 of 55
  • Radiology, Nuclear Medicine and Imaging 138
  • Artificial Intelligence 78
  • Biomedical Engineering 71
  • Health Informatics 57
  • Pulmonary and Respiratory Medicine 34
Replace Anna Seehofnerová with:
Anna Seehofnerová United States
Satyananda Kashyap United States
Jinchi Wei United States
Rongguo Zhang China
Huaiyu Wu China
Paul Hérent France
Andrea Lum Canada
Samuel J. Withey United Kingdom
Kexue Deng China
Andra-Iza Iuga Germany
Feyisope Eweje relative to Anna Seehofnerová United States Anna Seehofnerová's profile →
Citations per field
00.5×3.5×
Anna Seehofnerová · 1×
Citations per year

Countries citing papers authored by Feyisope Eweje

Since Specialization
Citations

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

Fields of papers citing papers by Feyisope Eweje

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Feyisope Eweje

This figure shows the co-authorship network connecting the top 25 collaborators of Feyisope Eweje. A scholar is included among the top collaborators of Feyisope Eweje based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Feyisope Eweje. Feyisope Eweje is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

9 of 9 papers shown
#WorkIndexed citations
1 0
2
A vision–language foundation model for precision oncologybreakdown →
48
3 0
4 5
5 6
6 20
7 74
8 6
9 80

About Feyisope Eweje

Feyisope Eweje is a scholar working on Health Informatics, Radiology, Nuclear Medicine and Imaging and Biophysics, having authored 9 papers that have together received 239 indexed citations. Recurring topics across this work include Radiomics and Machine Learning in Medical Imaging (6 papers), AI in cancer detection (3 papers) and Medical Imaging and Pathology Studies (2 papers). The work is most often cited by research in Health Informatics (57 citations), Radiology, Nuclear Medicine and Imaging (138 citations) and Toxicology (9 citations). Feyisope Eweje has collaborated with scholars based in United States and China. Frequent co-authors include Yu He, Harrison X. Bai, Jing Wu, Lisa J. States, Ronnie Sebro, Xianjing Peng, Shaolei Lu, Paul Zhang, Yongheng Luo and Weihua Liao. Their work appears in journals such as Nature, Nature Medicine and Nature Communications.

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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