Adi Szeskin
Impact in
- Health Informatics top 2%
- Artificial Intelligence in Healthcare and Education
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- Medical Image Segmentation Techniques
- Advanced Neural Network Applications
Papers in
-
- Radiomics and Machine Learning in Medical Imaging 3
- Retinal Imaging and Analysis 2
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- Medical Image Segmentation Techniques 5
- Co-authors
- Leo Joskowicz B (9 shared papers)Jacob Sosna (5 shared papers)Naama Lev‐Cohain (1 shared paper)Refael Vivanti (1 shared paper)Jaime Levy (3 shared papers)Arnaldo Mayer (1 shared paper)Iris Eshed (1 shared paper)Assaf Ben‐Meir (1 shared paper)
- Journals
- Medical Image Analysis (4 papers)International Journal of Computer Assisted Radiology and Surgery (2 papers)European Radiology (1 paper)Journal of Thoracic Imaging (1 paper)Translational Vision Science & Technology (1 paper)
- Partner nations
- IsraelGermanySwitzerland
In The Last Decade
Adi Szeskin
12 papers receiving 979 citations
Adi Szeskin's Hit Papers
Peers
Comparison fields: 5 of 48
- Health Informatics 87
- Computer Vision and Pattern Recognition 697
- Artificial Intelligence 247
- Radiology, Nuclear Medicine and Imaging 132
- Reproductive Medicine 19
Countries citing papers authored by Adi Szeskin
This map shows the geographic impact of Adi Szeskin'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 Adi Szeskin with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Adi Szeskin more than expected).
Fields of papers citing papers by Adi Szeskin
This network shows the impact of papers produced by Adi Szeskin. 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 Adi Szeskin. The network helps show where Adi Szeskin may publish in the future.
Co-authors
The 16 scholars most cited alongside Adi Szeskin, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | The Liver Tumor Segmentation Benchmark (LiTS) Hit paper breakdown → | 2022 | 797 |
| 2 | 2017 | 61 | |
| 3 | 2019 | 26 | |
| 4 | 2021 | 25 | |
| 5 | 2020 | 24 | |
| 6 | 2022 | 24 | |
| 7 | 2022 | 11 | |
| 8 | 2023 | 11 | |
| 9 | 2017 | 7 | |
| 10 | 2023 | 6 | |
| 11 | 2024 | 1 | |
| 12 | 2024 | 1 |
About Adi Szeskin
Adi Szeskin is a scholar working on Radiology, Nuclear Medicine and Imaging, Computer Vision and Pattern Recognition, Ophthalmology, Reproductive Medicine and Artificial Intelligence, having authored 12 papers that have together received 994 indexed citations. Recurring topics across this work include Medical Image Segmentation Techniques (5 papers), Radiomics and Machine Learning in Medical Imaging (3 papers), AI in cancer detection (2 papers), Retinal Diseases and Treatments (2 papers), Retinal Imaging and Analysis (2 papers), Medical Imaging and Analysis (1 paper), Reproductive Health and Technologies (1 paper) and Nanomaterials and Printing Technologies (1 paper). The work is most often cited by research in Health Informatics (87 citations), Computer Vision and Pattern Recognition (697 citations), Artificial Intelligence (247 citations), Radiology, Nuclear Medicine and Imaging (132 citations) and Reproductive Medicine (19 citations). Adi Szeskin has collaborated with scholars based in Israel, Germany and Switzerland. Frequent co-authors include Leo Joskowicz B, Jacob Sosna, Naama Lev‐Cohain, Refael Vivanti, Jaime Levy, Arnaldo Mayer, Iris Eshed, Assaf Ben‐Meir, Iris Har‐Vardi and Amnon Buxboim. Their work appears in journals such as Medical Image Analysis, International Journal of Computer Assisted Radiology and Surgery, European Radiology, Journal of Thoracic Imaging and Translational Vision Science & Technology.
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.