Adi Szeskin

1.6k total citations
11 papers, 173 citations indexed

About

Adi Szeskin is a scholar working on Radiology, Nuclear Medicine and Imaging, Ophthalmology and Artificial Intelligence. According to data from OpenAlex, Adi Szeskin has authored 11 papers receiving a total of 173 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Radiology, Nuclear Medicine and Imaging, 3 papers in Ophthalmology and 3 papers in Artificial Intelligence. Recurrent topics in Adi Szeskin's work include Radiomics and Machine Learning in Medical Imaging (4 papers), Retinal Imaging and Analysis (3 papers) and AI in cancer detection (3 papers). Adi Szeskin is often cited by papers focused on Radiomics and Machine Learning in Medical Imaging (4 papers), Retinal Imaging and Analysis (3 papers) and AI in cancer detection (3 papers). Adi Szeskin collaborates with scholars based in Israel. Adi Szeskin's co-authors include Leo Joskowicz, Jacob Sosna, Refael Vivanti, Naama Lev‐Cohain, Jaime Levy, Richard J. Lederman, Iris Eshed, Arnaldo Mayer, Iris Har‐Vardi and Matan Gavish and has published in prestigious journals such as SHILAP Revista de lepidopterología, Medical Image Analysis and European Radiology.

In The Last Decade

Adi Szeskin

10 papers receiving 167 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Adi Szeskin Israel 8 92 40 38 28 19 11 173
Jinchi Wei United States 11 144 1.6× 55 1.4× 84 2.2× 44 1.6× 6 0.3× 22 316
Fred Nugen United States 6 93 1.0× 36 0.9× 46 1.2× 8 0.3× 5 0.3× 10 174
Christian Bracco Italy 9 243 2.6× 43 1.1× 48 1.3× 2 0.1× 5 0.3× 26 334
Sunny Virmani United States 7 172 1.9× 22 0.6× 18 0.5× 82 2.9× 7 0.4× 10 254
Yassir Edrees Almalki Saudi Arabia 8 136 1.5× 100 2.5× 35 0.9× 7 0.3× 4 0.2× 32 258
Saad Khan United Kingdom 5 157 1.7× 37 0.9× 16 0.4× 111 4.0× 15 0.8× 7 263
Gary Brahm Canada 7 95 1.0× 17 0.4× 48 1.3× 4 0.1× 12 0.6× 13 206
Yasuhisa Kurata Japan 11 152 1.7× 50 1.3× 30 0.8× 15 0.8× 44 396

Countries citing papers authored by Adi Szeskin

Since Specialization
Citations

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

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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-authorship network of co-authors of Adi Szeskin

This figure shows the co-authorship network connecting the top 25 collaborators of Adi Szeskin. A scholar is included among the top collaborators of Adi Szeskin 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 Adi Szeskin. Adi Szeskin is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

11 of 11 papers shown
1.
2.
Szeskin, Adi, et al.. (2024). Metastatic Lung Lesion Changes in Follow-up Chest CT. Journal of Thoracic Imaging. 40(2). 1 indexed citations
3.
Joskowicz, Leo, et al.. (2023). Follow-up of liver metastases: a comparison of deep learning and RECIST 1.1. European Radiology. 33(12). 9320–9327. 11 indexed citations
4.
Szeskin, Adi, et al.. (2023). Graph-based automatic detection and classification of lesion changes in pairs of CT studies for oncology follow-up. International Journal of Computer Assisted Radiology and Surgery. 19(2). 241–251. 4 indexed citations
5.
Szeskin, Adi, et al.. (2022). Liver lesion changes analysis in longitudinal CECT scans by simultaneous deep learning voxel classification with SimU-Net. Medical Image Analysis. 83. 102675–102675. 15 indexed citations
6.
Szeskin, Adi, et al.. (2022). Progression of cRORA (Complete RPE and Outer Retinal Atrophy) in Dry Age-Related Macular Degeneration Measured Using SD-OCT. Translational Vision Science & Technology. 11(1). 19–19. 11 indexed citations
7.
Szeskin, Adi, et al.. (2021). A column-based deep learning method for the detection and quantification of atrophy associated with AMD in OCT scans. Medical Image Analysis. 72. 102130–102130. 23 indexed citations
8.
Szeskin, Adi, Yuval Or, Zeev Shoham, et al.. (2020). Automated Evaluation of Human Embryo Blastulation and Implantation Potential using Deep‐Learning. SHILAP Revista de lepidopterología. 2(10). 23 indexed citations
9.
Joskowicz, Leo, et al.. (2019). Automatic detection and diagnosis of sacroiliitis in CT scans as incidental findings. Medical Image Analysis. 57. 165–175. 23 indexed citations
10.
Vivanti, Refael, Adi Szeskin, Naama Lev‐Cohain, Jacob Sosna, & Leo Joskowicz. (2017). Automatic detection of new tumors and tumor burden evaluation in longitudinal liver CT scan studies. International Journal of Computer Assisted Radiology and Surgery. 12(11). 1945–1957. 55 indexed citations
11.
Rosen, Isaac, et al.. (2017). Copper interconnections and antennas fabricated by hot-pressing printed copper formate. Flexible and Printed Electronics. 2(3). 35007–35007. 7 indexed citations

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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