Miso Jang

22 papers receiving 657 citations

Peers

Miso Jang
Comparison fields: 5 of 80
  • Health Informatics 27
  • Aerospace Engineering 311
  • Mechanical Engineering 392
  • Orthopedics and Sports Medicine 55
  • Radiology, Nuclear Medicine and Imaging 64
Replace Anindya Lahiri with:
Anindya Lahiri United Kingdom
Asaki Hattori Japan
Brian Baillargeon United States
J. Zuhars United States
Nuno Rebelo United States
P. Gomes United Kingdom
M. Jakopec United Kingdom
Zh. Zhang China
Rodrigo Moreno Sweden
Myung Hyun Kim South Korea
Miso Jang relative to Anindya Lahiri United Kingdom Anindya Lahiri's profile →
Citations per field
00.5×10×14.1×
Anindya Lahiri · 1×
Citations per year

Countries citing papers authored by Miso Jang

Since Specialization
Citations

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

Fields of papers citing papers by Miso Jang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Miso Jang, 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 Miso Jang Line = papers co-authored together Miso Jang links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 24 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2017209
2 2016187
3 202065
4 201832
5 202225
6 202323
7 202019
8 202316
9 202014
10 200614
11 202311
12 201811
13 20219
14 20179
15 20246
16 20186
17 20233
18 20183
19 20222
20 20242

About Miso Jang

Miso Jang is a scholar working on Radiology, Nuclear Medicine and Imaging, Health Informatics, Orthopedics and Sports Medicine, Computer Vision and Pattern Recognition and Health, Toxicology and Mutagenesis, having authored 24 papers that have together received 668 indexed citations. Recurring topics across this work include Bone health and osteoporosis research (4 papers), COVID-19 diagnosis using AI (4 papers), Radiomics and Machine Learning in Medical Imaging (4 papers), Artificial Intelligence in Healthcare and Education (4 papers), High-Temperature Coating Behaviors (2 papers), Climate Change and Health Impacts (2 papers), Air Quality and Health Impacts (2 papers) and High Entropy Alloys Studies (2 papers). The work is most often cited by research in Health Informatics (27 citations), Aerospace Engineering (311 citations), Mechanical Engineering (392 citations), Orthopedics and Sports Medicine (55 citations) and Radiology, Nuclear Medicine and Imaging (64 citations). Miso Jang has collaborated with scholars based in South Korea, Japan and Ethiopia. Frequent co-authors include Hyoung Seop Kim, Soo‐Hyun Joo, Hidemi Kato, Jongun Moon, Che‐Wei Tsai, J.W. Yeh, Namkug Kim, Soon‐Jik Hong, Mingyu Kim and Jung‐Min Koh. Their work appears in journals such as Scientific Reports, Korean Journal of Radiology, BMC Endocrine Disorders, Journal of Alloys and Compounds and Materials Science and Engineering A.

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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