Hyunkwang Lee

2.5k total citations · 2 hit papers
15 papers, 1.7k citations indexed

About

Hyunkwang Lee is a scholar working on Radiology, Nuclear Medicine and Imaging, Electrical and Electronic Engineering and Biomedical Engineering. According to data from OpenAlex, Hyunkwang Lee has authored 15 papers receiving a total of 1.7k indexed citations (citations by other indexed papers that have themselves been cited), including 4 papers in Radiology, Nuclear Medicine and Imaging, 4 papers in Electrical and Electronic Engineering and 4 papers in Biomedical Engineering. Recurrent topics in Hyunkwang Lee's work include Advanced Memory and Neural Computing (4 papers), Radiomics and Machine Learning in Medical Imaging (3 papers) and AI in cancer detection (2 papers). Hyunkwang Lee is often cited by papers focused on Advanced Memory and Neural Computing (4 papers), Radiomics and Machine Learning in Medical Imaging (3 papers) and AI in cancer detection (2 papers). Hyunkwang Lee collaborates with scholars based in United States and Germany. Hyunkwang Lee's co-authors include Synho Do, Shahein Tajmir, Gu-Yeon Wei, Saketh Rama, David Brooks, Sae Kyu Lee, Brandon Reagen, Paul N. Whatmough, José Miguel Hernández-Lobato and Robert Adolf and has published in prestigious journals such as Scientific Reports, Nature Biomedical Engineering and Skeletal Radiology.

In The Last Decade

Hyunkwang Lee

15 papers receiving 1.7k citations

Hit Papers

Fully Automated Deep Learning System for Bone Age Assessment 2017 2026 2020 2023 2017 2018 100 200 300
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.

  1. Fully Automated Deep Learning System for Bone Age Assessment
    2017 319 citations Hyunkwang Lee, Shahein Tajmir et al. Journal of Digital Imaging profile →
  2. An explainable deep-learning algorithm for the detection of acute intracranial haemorrhage from small datasets
    2018 309 citations Hyunkwang Lee, Sehyo Yune et al. Nature Biomedical Engineering profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Hyunkwang Lee United States 13 473 451 450 419 270 15 1.7k
Jitae Shin South Korea 17 590 1.2× 76 0.2× 135 0.3× 281 0.7× 70 0.3× 123 1.2k
Syoji Kobashi Japan 18 64 0.1× 226 0.5× 272 0.6× 488 1.2× 426 1.6× 273 1.5k
Kuo‐Sheng Cheng Taiwan 20 549 1.2× 223 0.5× 190 0.4× 253 0.6× 318 1.2× 97 1.8k
Awni Hannun Israel 9 82 0.2× 595 1.3× 251 0.6× 127 0.3× 372 1.4× 16 2.2k
Carlos A. Silva Portugal 20 38 0.1× 836 1.9× 1.1k 2.5× 1.6k 3.7× 377 1.4× 55 3.1k
Hong Song China 17 49 0.1× 268 0.6× 444 1.0× 562 1.3× 315 1.2× 182 1.4k
Sanghoon Jun South Korea 10 74 0.2× 354 0.8× 487 1.1× 201 0.5× 191 0.7× 27 1.2k
Yuyin Zhou United States 23 116 0.2× 1.4k 3.1× 712 1.6× 1.1k 2.6× 226 0.8× 49 2.4k
C. Kambhampati United Kingdom 15 56 0.1× 364 0.8× 180 0.4× 59 0.1× 85 0.3× 73 1.3k

Countries citing papers authored by Hyunkwang Lee

Since Specialization
Citations

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

Fields of papers citing papers by Hyunkwang Lee

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Hyunkwang Lee

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

All Works

15 of 15 papers shown
1.
Grisot, Giorgia, et al.. (2024). Impact of a Categorical AI System for Digital Breast Tomosynthesis on Breast Cancer Interpretation by Both General Radiologists and Breast Imaging Specialists. Radiology Artificial Intelligence. 6(2). e230137–e230137. 7 indexed citations
2.
Lee, Hyunkwang, Chao Huang, Sehyo Yune, et al.. (2019). Machine Friendly Machine Learning: Interpretation of Computed Tomography Without Image Reconstruction. Scientific Reports. 9(1). 15540–15540. 33 indexed citations
3.
Parakh, Anushri, Hyunkwang Lee, Jeong Hyun Lee, et al.. (2019). Urinary Stone Detection on CT Images Using Deep Convolutional Neural Networks: Evaluation of Model Performance and Generalization. Radiology Artificial Intelligence. 1(4). e180066–e180066. 82 indexed citations
4.
Tajmir, Shahein, Hyunkwang Lee, Randheer Shailam, et al.. (2018). Artificial intelligence-assisted interpretation of bone age radiographs improves accuracy and decreases variability. Skeletal Radiology. 48(2). 275–283. 89 indexed citations
5.
Yune, Sehyo, Hyunkwang Lee, Myeongchan Kim, et al.. (2018). Beyond Human Perception: Sexual Dimorphism in Hand and Wrist Radiographs Is Discernible by a Deep Learning Model. Journal of Digital Imaging. 32(4). 665–671. 30 indexed citations
6.
Finlayson, Samuel G., Hyunkwang Lee, Isaac S. Kohane, & Luke Oakden‐Rayner. (2018). Towards generative adversarial networks as a new paradigm for radiology education. arXiv (Cornell University). 1 indexed citations
7.
Lee, Hyunkwang, Sehyo Yune, Mohammad Mansouri, et al.. (2018). An explainable deep-learning algorithm for the detection of acute intracranial haemorrhage from small datasets. Nature Biomedical Engineering. 3(3). 173–182. 309 indexed citations breakdown →
8.
Lee, Hyunkwang, et al.. (2017). 14.3 A 28nm SoC with a 1.2GHz 568nJ/prediction sparse deep-neural-network engine with >0.1 timing error rate tolerance for IoT applications. IEEE Conference Proceedings. 2017. 243. 56 indexed citations
9.
Lee, Hyunkwang, Fabian M. Troschel, Shahein Tajmir, et al.. (2017). Pixel-Level Deep Segmentation: Artificial Intelligence Quantifies Muscle on Computed Tomography for Body Morphometric Analysis. Journal of Digital Imaging. 30(4). 487–498. 123 indexed citations
10.
Lee, Hyunkwang, Mohammad Mansouri, Shahein Tajmir, Michael H. Lev, & Synho Do. (2017). A Deep-Learning System for Fully-Automated Peripherally Inserted Central Catheter (PICC) Tip Detection. Journal of Digital Imaging. 31(4). 393–402. 39 indexed citations
11.
Lee, Hyunkwang, Shahein Tajmir, Jenny Lee, et al.. (2017). Fully Automated Deep Learning System for Bone Age Assessment. Journal of Digital Imaging. 30(4). 427–441. 319 indexed citations breakdown →
12.
Whatmough, Paul N., Sae Kyu Lee, Hyunkwang Lee, et al.. (2017). 14.3 A 28nm SoC with a 1.2GHz 568nJ/prediction sparse deep-neural-network engine with >0.1 timing error rate tolerance for IoT applications. 242–243. 119 indexed citations
13.
Reagen, Brandon, Paul N. Whatmough, Robert Adolf, et al.. (2016). Minerva. ACM SIGARCH Computer Architecture News. 44(3). 267–278. 305 indexed citations
14.
Reagen, Brandon, Paul N. Whatmough, Robert Adolf, et al.. (2016). Minerva: Enabling Low-Power, Highly-Accurate Deep Neural Network Accelerators. 267–278. 178 indexed citations
15.
Zhang, Xuan, Sae Kyu Lee, Brandon Reagen, et al.. (2015). A multi-chip system optimized for insect-scale flapping-wing robots. C152–C153. 14 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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