J. Shin

3.8k total citations · 1 hit paper
7 papers, 2.5k citations indexed

About

J. Shin is a scholar working on Computer Vision and Pattern Recognition, Radiology, Nuclear Medicine and Imaging and Artificial Intelligence. According to data from OpenAlex, J. Shin has authored 7 papers receiving a total of 2.5k indexed citations (citations by other indexed papers that have themselves been cited), including 4 papers in Computer Vision and Pattern Recognition, 4 papers in Radiology, Nuclear Medicine and Imaging and 3 papers in Artificial Intelligence. Recurrent topics in J. Shin's work include COVID-19 diagnosis using AI (3 papers), Machine Learning and Algorithms (2 papers) and Cardiovascular Health and Disease Prevention (2 papers). J. Shin is often cited by papers focused on COVID-19 diagnosis using AI (3 papers), Machine Learning and Algorithms (2 papers) and Cardiovascular Health and Disease Prevention (2 papers). J. Shin collaborates with scholars based in United States. J. Shin's co-authors include Jianming Liang, Michael B. Gotway, Suryakanth Gurudu, Nima Tajbakhsh, R. Todd Hurst, Christopher B. Kendall, Zongwei Zhou, Lei Zhang and Ruibin Feng and has published in prestigious journals such as IEEE Transactions on Medical Imaging, Medical Image Analysis and Journal of Digital Imaging.

In The Last Decade

J. Shin

7 papers receiving 2.5k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Convolutional Neural Networks for Medical Image Analysis: Full Training or Fine Tuning?

2016 2.1k citations Nima Tajbakhsh, J. Shin et al. IEEE Transactions on Medical Imaging profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
J. Shin United States	7	1.1k	1.0k	848	271	246	7	2.5k
María A. Zuluaga France	19	988 0.9×	705 0.7×	818 1.0×	290 1.1×	224 0.9×	76	2.4k
Ozan Oktay United Kingdom	16	817 0.7×	1.3k 1.2×	1.3k 1.5×	475 1.8×	324 1.3×	29	2.7k
Isabella Nogues United States	4	1.5k 1.4×	1.5k 1.5×	1.1k 1.3×	460 1.7×	290 1.2×	6	4.1k
Nabil Ibtehaz Bangladesh	15	644 0.6×	795 0.8×	804 0.9×	425 1.6×	270 1.1×	29	2.2k
Md Zahangir Alom United States	16	1.3k 1.2×	950 0.9×	1.1k 1.3×	252 0.9×	254 1.0×	63	3.3k
Yi Guo China	30	757 0.7×	1.5k 1.5×	588 0.7×	474 1.7×	173 0.7×	163	3.5k
Burhan Ergen Türkiye	25	1.2k 1.0×	1.1k 1.1×	878 1.0×	151 0.6×	477 1.9×	90	2.6k
Leonardo Rundo Italy	33	1.2k 1.1×	1.4k 1.3×	1.0k 1.2×	423 1.6×	518 2.1×	102	3.3k
Xin Yang China	21	1.2k 1.0×	1.5k 1.4×	1.2k 1.4×	587 2.2×	264 1.1×	86	3.1k
Christian Desrosiers Canada	25	748 0.7×	1.1k 1.0×	991 1.2×	349 1.3×	281 1.1×	144	2.7k

Countries citing papers authored by J. Shin

Since Specialization

Citations

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

Fields of papers citing papers by J. Shin

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of J. Shin

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

All Works

Sort: Min cites: Since: Top N: Style:

7 of 7 papers shown

1.

Zhou, Zongwei, J. Shin, Suryakanth Gurudu, Michael B. Gotway, & Jianming Liang. (2021). Active, continual fine tuning of convolutional neural networks for reducing annotation efforts. Medical Image Analysis. 71. 101997–101997. 38 indexed citations

2.

Tajbakhsh, Nima, J. Shin, Michael B. Gotway, & Jianming Liang. (2019). Computer-aided detection and visualization of pulmonary embolism using a novel, compact, and discriminative image representation. Medical Image Analysis. 58. 101541–101541. 44 indexed citations

3.

Zhou, Zongwei, J. Shin, Ruibin Feng, et al.. (2018). Integrating Active Learning and Transfer Learning for Carotid Intima-Media Thickness Video Interpretation. Journal of Digital Imaging. 32(2). 290–299. 22 indexed citations

4.

Shin, J., et al.. (2017). Automatic polyp detection in colonoscopy videos. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 10133. 101332K–101332K. 23 indexed citations

5.

Zhou, Zongwei, J. Shin, Lei Zhang, et al.. (2017). Fine-Tuning Convolutional Neural Networks for Biomedical Image Analysis: Actively and Incrementally. Europe PMC (PubMed Central). 4761–4772. 294 indexed citations

6.

Tajbakhsh, Nima, J. Shin, Suryakanth Gurudu, et al.. (2016). Convolutional Neural Networks for Medical Image Analysis: Full Training or Fine Tuning?. IEEE Transactions on Medical Imaging. 35(5). 1299–1312. 2079 indexed citations breakdown →

7.

Shin, J., Nima Tajbakhsh, R. Todd Hurst, Christopher B. Kendall, & Jianming Liang. (2016). Automating Carotid Intima-Media Thickness Video Interpretation with Convolutional Neural Networks. 2526–2535. 46 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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