Hyeonseob Nam

6.6k total citations · 2 hit papers
9 papers, 1.1k citations indexed

About

Hyeonseob Nam is a scholar working on Artificial Intelligence, Radiology, Nuclear Medicine and Imaging and Computer Vision and Pattern Recognition. According to data from OpenAlex, Hyeonseob Nam has authored 9 papers receiving a total of 1.1k indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Artificial Intelligence, 5 papers in Radiology, Nuclear Medicine and Imaging and 3 papers in Computer Vision and Pattern Recognition. Recurrent topics in Hyeonseob Nam's work include Radiomics and Machine Learning in Medical Imaging (5 papers), AI in cancer detection (4 papers) and Domain Adaptation and Few-Shot Learning (3 papers). Hyeonseob Nam is often cited by papers focused on Radiomics and Machine Learning in Medical Imaging (5 papers), AI in cancer detection (4 papers) and Domain Adaptation and Few-Shot Learning (3 papers). Hyeonseob Nam collaborates with scholars based in South Korea. Hyeonseob Nam's co-authors include Jeonghee Kim, Jung-Woo Ha, Hyoeun Kim, Hyunjae Lee, Eun Hye Lee, Eun‐Kyung Kim, Kihwan Kim, Boo‐Kyung Han, Hak Hee Kim and Kyunghwa Han and has published in prestigious journals such as Journal of Clinical Oncology, The Lancet Digital Health and Radiology Artificial Intelligence.

In The Last Decade

Hyeonseob Nam

8 papers receiving 1.0k 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.

Dual Attention Networks for Multimodal Reasoning and Matching

2017 497 citations Hyeonseob Nam, Jung-Woo Ha et al. profile →
Changes in cancer detection and false-positive recall in mammography using artificial intelligence: a retrospective, multireader study

2020 309 citations Hak Hee Kim, Boo‐Kyung Han et al. The Lancet Digital Health profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Hyeonseob Nam South Korea	6	649	590	281	108	84	9	1.1k
Marcelo Zanchetta do Nascimento Brazil	17	682 1.1×	508 0.9×	338 1.2×	23 0.2×	42 0.5×	91	997
Tanvir Mahmud Bangladesh	13	373 0.6×	177 0.3×	480 1.7×	83 0.8×	90 1.1×	32	774
Basil Mustafa Switzerland	5	393 0.6×	346 0.6×	247 0.9×	32 0.3×	33 0.4×	6	810
Ali Mottaghi United States	4	235 0.4×	173 0.3×	229 0.8×	103 1.0×	51 0.6×	5	743
Hideki Nakayama Japan	16	650 1.0×	702 1.2×	234 0.8×	25 0.2×	55 0.7×	78	1.2k
Jintai Chen China	14	267 0.4×	310 0.5×	165 0.6×	29 0.3×	45 0.5×	38	701
Sirui Ding China	5	422 0.7×	320 0.5×	138 0.5×	43 0.4×	22 0.3×	11	820
Qiu Guan China	14	322 0.5×	388 0.7×	228 0.8×	20 0.2×	32 0.4×	75	860
Changhee Han Japan	10	316 0.5×	325 0.6×	249 0.9×	27 0.3×	63 0.8×	27	762

Countries citing papers authored by Hyeonseob Nam

Since Specialization

Citations

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

Fields of papers citing papers by Hyeonseob Nam

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Hyeonseob Nam

This figure shows the co-authorship network connecting the top 25 collaborators of Hyeonseob Nam. A scholar is included among the top collaborators of Hyeonseob Nam 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 Hyeonseob Nam. Hyeonseob Nam 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:

9 of 9 papers shown

1.

Lee, Hyunjae, et al.. (2023). Transformer-based Deep Neural Network for Breast Cancer Classification on Digital Breast Tomosynthesis Images. Radiology Artificial Intelligence. 5(3). e220159–e220159. 21 indexed citations

2.

Park, Eun Kyung, Minjeong Kim, Ki Hwan Kim, et al.. (2022). Robust artificial intelligence-powered imaging biomarker based on mammography for risk prediction of breast cancer.. Journal of Clinical Oncology. 40(16_suppl). 10533–10533.

3.

Kim, Ki Hwan, et al.. (2021). Development of AI-powered imaging biomarker for breast cancer risk assessment on the basis of mammography alone.. Journal of Clinical Oncology. 39(15_suppl). 10519–10519. 4 indexed citations

4.

Nam, Hyeonseob, Ki Hwan Kim, & Chan‐Young Ock. (2021). AI-based imaging biomarker in mammography for prediction of tumor invasiveness.. Journal of Clinical Oncology. 39(15_suppl). 1568–1568. 1 indexed citations

5.

Kim, Hak Hee, Boo‐Kyung Han, Kihwan Kim, et al.. (2020). Changes in cancer detection and false-positive recall in mammography using artificial intelligence: a retrospective, multireader study. The Lancet Digital Health. 2(3). e138–e148. 309 indexed citations breakdown →

6.

Lee, Hyunjae, Hyoeun Kim, & Hyeonseob Nam. (2019). SRM: A Style-Based Recalibration Module for Convolutional Neural Networks. 1854–1862. 192 indexed citations

7.

Nam, Hyeonseob, et al.. (2019). Reducing Domain Gap via Style-Agnostic Networks.. 14 indexed citations

8.

Nam, Hyeonseob & Hyoeun Kim. (2018). Batch-Instance Normalization for Adaptively Style-Invariant Neural Networks. Neural Information Processing Systems. 31. 2558–2567. 34 indexed citations

9.

Nam, Hyeonseob, Jung-Woo Ha, & Jeonghee Kim. (2017). Dual Attention Networks for Multimodal Reasoning and Matching. 2156–2164. 497 indexed citations breakdown →

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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