Jae Kwon Kim

649 citations
41 papers · 464 indexed · h-index 11
Topics
Silicon Nanostructures and Photoluminescence (6 papers)AI in cancer detection (5 papers)Prostate Cancer Diagnosis and Treatment (4 papers)

In The Last Decade

Jae Kwon Kim

36 papers receiving 438 citations

Peers

Jae Kwon Kim
Comparison fields: 5 of 104
  • Electrical and Electronic Engineering 115
  • Health Information Management 112
  • Artificial Intelligence 93
  • Materials Chemistry 80
  • Biomedical Engineering 49
Replace M. Srinivas with:
M. Srinivas India
Chih‐Wen Cheng United States
Amr E. Mohamed Egypt
Ahmad P. Tafti United States
António Garrido Spain
Jamal Alhiyafi Saudi Arabia
Heba Mamdouh Farghaly Egypt
Omid Rajabi Shishvan United States
Ali Haider Khan Pakistan
Gokul Krishnan India
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Citations per field
00.5×1.5×2.4×
M. Srinivas · 1×
Citations per year

Countries citing papers authored by Jae Kwon Kim

Since Specialization
Citations

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

Fields of papers citing papers by Jae Kwon Kim

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jae Kwon Kim. 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 Jae Kwon Kim. The network helps show where Jae Kwon Kim may publish in the future.

Co-authorship network of co-authors of Jae Kwon Kim

This figure shows the co-authorship network connecting the top 25 collaborators of Jae Kwon Kim. A scholar is included among the top collaborators of Jae Kwon Kim 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 Jae Kwon Kim. Jae Kwon Kim 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
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9
A Performance Comparison on the Machine Learning Classifiers in Predictive Pathology Staging of Prostate Cancer.
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10 92
11 7
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Reverse Auction-based Resource Allocation Policy for Service Broker in Hybrid Cloud Environment
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13 1
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17 5
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Rapid Thermal Annealing Eect on Charge Storage Characteristics in MOS Capacitor with Ge Nanocrystals
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20 8

About Jae Kwon Kim

Jae Kwon Kim is a scholar working on Health Information Management, Health Informatics and Safety Research, having authored 41 papers that have together received 464 indexed citations. Recurring topics across this work include Silicon Nanostructures and Photoluminescence (6 papers), AI in cancer detection (5 papers) and Prostate Cancer Diagnosis and Treatment (4 papers). The work is most often cited by research in Health Information Management (112 citations), Health Informatics (14 citations) and Medical Laboratory Technology (7 citations). Jae Kwon Kim has collaborated with scholars based in South Korea, United States and India. Frequent co-authors include Sanggil Kang, Yong Kim, Jae-Yel Yi, Young Shin Han, Seokhwan Bang, Jaehee Cho, Kyungyong Chung, In Young Choi, Daesung Lee and Jonghun Kim. Their work appears in journals such as Applied Physics Letters, PLoS ONE and Journal of Alloys and Compounds.

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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