Yongsik Sim

449 citations
18 papers · 274 indexed · h-index 8
Topics
Radiomics and Machine Learning in Medical Imaging (6 papers)Glioma Diagnosis and Treatment (4 papers)AI in cancer detection (4 papers)
Journals
SHILAP Revista de lepidopterologíaPLoS ONENeuroImage

In The Last Decade

Yongsik Sim

16 papers receiving 268 citations

Peers

Yongsik Sim
Comparison fields: 5 of 67
  • Radiology, Nuclear Medicine and Imaging 181
  • Pulmonary and Respiratory Medicine 99
  • Artificial Intelligence 79
  • Health Informatics 49
  • Biomedical Engineering 32
Replace Rongguo Zhang with:
Rongguo Zhang China
John Ryu United States
Gil-Sun Hong South Korea
Gilberto J. Aquino United States
Hanya Mahmood United Kingdom
Anne S. Chin United States
Reabal Najjar Australia
Dhakshinamoorthy Ganeshan United States
Heiko Peschl United Kingdom
Andra-Iza Iuga Germany
Yongsik Sim relative to Rongguo Zhang China Rongguo Zhang's profile →
Citations per field
00.5×1.7×
Rongguo Zhang · 1×
Citations per year

Countries citing papers authored by Yongsik Sim

Since Specialization
Citations

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

Fields of papers citing papers by Yongsik Sim

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Yongsik Sim

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

All Works

18 of 18 papers shown
#WorkIndexed citations
1 0
2 1
3 0
4 14
5 2
6 1
7 15
8 4
9 9
10 9
11 5
12 4
13 8
14 5
15 15
16 12
17 1
18 169

About Yongsik Sim

Yongsik Sim is a scholar working on Internal Medicine, Radiology, Nuclear Medicine and Imaging and Genetics, having authored 18 papers that have together received 274 indexed citations. Recurring topics across this work include Radiomics and Machine Learning in Medical Imaging (6 papers), Glioma Diagnosis and Treatment (4 papers) and AI in cancer detection (4 papers). The work is most often cited by research in Health Informatics (49 citations), Radiology, Nuclear Medicine and Imaging (181 citations) and Pulmonary and Respiratory Medicine (99 citations). Yongsik Sim has collaborated with scholars based in South Korea, United States and Singapore. Frequent co-authors include Kyunghwa Han, Elmar Kotter, Sehyo Yune, Byoung Wook Choi, Myung Jin Chung, Synho Do, Myeongchan Kim, Si Eun Lee, Sung‐Won Kim and Eun‐Kyung Kim. Their work appears in journals such as SHILAP Revista de lepidopterología, PLoS ONE and NeuroImage.

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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