Anna Jerebko

1.5k citations
34 papers · 932 · h-index 14

Impact in

Papers in

Anna Jerebko

34 papers receiving 893 citations

Peers

Anna Jerebko
Comparison fields: 5 of 91
  • Computer Science Applications 108
  • Radiology, Nuclear Medicine and Imaging 463
  • Oncology 350
  • Artificial Intelligence 397
  • Pulmonary and Respiratory Medicine 308
Replace Antonio Foncubierta–Rodríguez with:
Antonio Foncubierta–Rodríguez Switzerland
S.A. Karkanis Greece
Guangzhi Ma China
Lan Li China
Syed Furqan Qadri China
Jorge Bernal Spain
Oussama El Gannour Morocco
Amal Farag United States
Christoph Baur Germany
Anna Jerebko relative to Antonio Foncubierta–Rodríguez Switzerland Antonio Foncubierta–Rodríguez's profile →
Citations per field
00.5×8.8×
Antonio Foncubierta–Rodríguez · 1×
Citations per year

Countries citing papers authored by Anna Jerebko

Since Specialization
Citations

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

Fields of papers citing papers by Anna Jerebko

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 34 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2009232
2 2010143
3 2002106
4 200763
5 200361
6 200556
7 200254
8 200545
9 200629
10 200321
11 201318
12 201617
13 200715
14 200314
15 20038
16 20207
17 20126
18 20105
19 20174
20 20134

About Anna Jerebko

Anna Jerebko is a scholar working on Radiology, Nuclear Medicine and Imaging, Oncology, Pulmonary and Respiratory Medicine, Artificial Intelligence and Computer Vision and Pattern Recognition, having authored 34 papers that have together received 932 indexed citations. Recurring topics across this work include Colorectal Cancer Screening and Detection (16 papers), AI in cancer detection (12 papers), Medical Imaging Techniques and Applications (11 papers), Radiomics and Machine Learning in Medical Imaging (10 papers), Digital Radiography and Breast Imaging (8 papers), Image Retrieval and Classification Techniques (7 papers), Advanced X-ray and CT Imaging (5 papers) and Medical Image Segmentation Techniques (4 papers). The work is most often cited by research in Computer Science Applications (108 citations), Radiology, Nuclear Medicine and Imaging (463 citations), Oncology (350 citations), Artificial Intelligence (397 citations) and Pulmonary and Respiratory Medicine (308 citations). Anna Jerebko has collaborated with scholars based in United States, Germany and United Kingdom. Frequent co-authors include Ronald M. Summers, James D. Malley, Marek Franaszek, Luca Bogoni, C. Daniel Johnson, Shipeng Yu, Linda Moy, Toshiro Kubota, Marcos Salganicoff and Charles Florin. Their work appears in journals such as Medical Physics, Radiology, Academic Radiology, British Journal of Radiology and IEEE Journal of Biomedical and Health Informatics.

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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