Yujin Oh

2.0k citations
49 papers · 1.3k · 1 hit paper · h-index 13

Impact in

Papers in

Yujin Oh

35 papers receiving 1.3k citations

Yujin Oh's Hit Papers

Deep Learning COVID-19 Features on CXR Using Limited Training Data Sets. 2020 · 628 citations
6280+2+4Years since publication200400600

Peers

Yujin Oh
Comparison fields: 5 of 128
  • Health Informatics 134
  • Radiology, Nuclear Medicine and Imaging 684
  • Artificial Intelligence 426
  • Polymers and Plastics 125
  • General Dentistry 12
Replace Ying Song with:
Ying Song China
Tong Ding China
Michael Friebe Germany
Dahong Qian China
Yichi Zhang China
Yang Xiao China
Katy Blumer United States
Yabo Fu United States
Theodore Leng United States
Yujin Oh relative to Ying Song China Ying Song's profile →
Citations per field
00.5×4.3×
Ying Song · 1×
Citations per year

Countries citing papers authored by Yujin Oh

Since Specialization
Citations

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

Fields of papers citing papers by Yujin Oh

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Yujin Oh, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Yujin Oh Line = papers co-authored together Yujin Oh links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 49 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Deep Learning COVID-19 Features on CXR Using Limited Training Data Sets.
Hit paper breakdown →
2020628
2 2015157
3 202186
4 201261
5 202248
6 202041
7 201839
8 202434
9 201524
10 201322
11 201321
12 200413
13 202312
14 201111
15 201611
16 200411
17 202210
18 20189
19 20188
20
An analytical transformation technique for generating uniformly spaced computational mesh
19808

About Yujin Oh

Yujin Oh is a scholar working on Artificial Intelligence, Radiology, Nuclear Medicine and Imaging, Molecular Biology, Health, Toxicology and Mutagenesis and Computer Vision and Pattern Recognition, having authored 49 papers that have together received 1.3k indexed citations. Recurring topics across this work include Radiomics and Machine Learning in Medical Imaging (5 papers), Speech Recognition and Synthesis (5 papers), Speech and Audio Processing (4 papers), Indoor Air Quality and Microbial Exposure (3 papers), Air Quality and Health Impacts (3 papers), AI in cancer detection (3 papers), COVID-19 diagnosis using AI (3 papers) and Education, Safety, and Science Studies (2 papers). The work is most often cited by research in Health Informatics (134 citations), Radiology, Nuclear Medicine and Imaging (684 citations), Artificial Intelligence (426 citations), Polymers and Plastics (125 citations) and General Dentistry (12 citations). Yujin Oh has collaborated with scholars based in South Korea, United States and Russia. Frequent co-authors include Jong Chul Ye, Sang Joon Park, Sang Min Lee, Joon Beom Seo, Jea‐Gun Park, Sanghyo Lee, Jin Pyo Hong, WonBae Ko, Jung-Inn Sohn and Jongsun Lee. Their work appears in journals such as Medical Image Analysis, Journal of Cosmetic and Laser Therapy, IEEE Signal Processing Letters, Nature Communications and Applied Sciences.

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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