Inpyeong Hwang

1.5k citations
64 papers · 938 indexed · h-index 17
Topics
Radiomics and Machine Learning in Medical Imaging (18 papers)MRI in cancer diagnosis (13 papers)Glioma Diagnosis and Treatment (13 papers)
Journals
SHILAP Revista de lepidopterologíaClinical Infectious DiseasesScientific Reports

In The Last Decade

Inpyeong Hwang

58 papers receiving 920 citations

Peers

Inpyeong Hwang
Comparison fields: 5 of 89
  • Radiology, Nuclear Medicine and Imaging 511
  • Pulmonary and Respiratory Medicine 204
  • Surgery 160
  • Epidemiology 142
  • Genetics 114
Replace Daniel Appelbaum with:
Daniel Appelbaum United States
Reiichi Ishikura Japan
Yangsean Choi South Korea
Fulvio Zaccagna Italy
Se Jin Cho South Korea
Chih‐Chun Wu Taiwan
Daniel R. Simpson United States
Houman Sotoudeh United States
Ahmed E. Othman Germany
Michael Mayinger Switzerland
Inpyeong Hwang relative to Daniel Appelbaum United States Daniel Appelbaum's profile →
Citations per field
00.5×6.8×
Daniel Appelbaum · 1×
Citations per year

Countries citing papers authored by Inpyeong Hwang

Since Specialization
Citations

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

Fields of papers citing papers by Inpyeong Hwang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Inpyeong Hwang

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

All Works

20 of 20 papers shown
#WorkIndexed citations
1 4
2 0
3 0
4 1
5 1
6 1
7 0
8 4
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11 4
12 10
13 5
14 2
15 12
16 18
17 30
18 12
19 46
20 40

About Inpyeong Hwang

Inpyeong Hwang is a scholar working on Radiology, Nuclear Medicine and Imaging, Genetics and Neurology, having authored 64 papers that have together received 938 indexed citations. Recurring topics across this work include Radiomics and Machine Learning in Medical Imaging (18 papers), MRI in cancer diagnosis (13 papers) and Glioma Diagnosis and Treatment (13 papers). The work is most often cited by research in Radiology, Nuclear Medicine and Imaging (511 citations), Health Informatics (29 citations) and Hepatology (108 citations). Inpyeong Hwang has collaborated with scholars based in South Korea, Ethiopia and Puerto Rico. Frequent co-authors include Ji‐hoon Kim, Tae Jin Yun, Chul‐Ho Sohn, Koung Mi Kang, Roh‐Eul Yoo, Seung Hong Choi, Byung Ihn Choi, Jeong Min Lee, Jeong Hee Yoon and Joon Koo Han. Their work appears in journals such as SHILAP Revista de lepidopterología, Clinical Infectious Diseases and Scientific Reports.

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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