Bin‐Na Kim

523 citations
41 papers · 377 · h-index 10

Impact in

Papers in

    • Child and Adolescent Psychosocial and Emotional Development 5
    • COVID-19 and Mental Health 4
    • Posttraumatic Stress Disorder Research 3
    • Anxiety, Depression, Psychometrics, Treatment, Cognitive Processes 4
    • Mental Health Research Topics 4

Bin‐Na Kim

37 papers receiving 363 citations

Peers

Bin‐Na Kim
Comparison fields: 5 of 96
  • Experimental and Cognitive Psychology 63
  • Biological Psychiatry 11
  • Clinical Psychology 75
  • Health Informatics 5
  • Applied Psychology 15
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Valerio Manippa Italy
Shin Ho Park Australia
F.S. Albuquerque Brazil
Mounir Ouzir Morocco
Jessica L. King United States
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Olga Raz Israel
David García‐Burgos Spain
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Citations per field
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Citations per year

Countries citing papers authored by Bin‐Na Kim

Since Specialization
Citations

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

Fields of papers citing papers by Bin‐Na Kim

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Bin‐Na 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 Bin‐Na Kim. The network helps show where Bin‐Na Kim may publish in the future.

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 41 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2016103
2 201627
3 201420
4 201417
5 202117
6 202116
7 202114
8
Deep learning-based diagnosis of lung cancer using a nationwide respiratory cytology image set: improving accuracy and inter-observer variability.
202312
9 201711
10 201911
11 201210
12 201710
13 201710
14 20119
15 20209
16 20098
17 20237
18 20177
19 20147
20 20107

About Bin‐Na Kim

Bin‐Na Kim is a scholar working on Clinical Psychology, Experimental and Cognitive Psychology, Psychiatry and Mental health, Food Science and Ecology, Evolution, Behavior and Systematics, having authored 41 papers that have together received 377 indexed citations. Recurring topics across this work include Bipolar Disorder and Treatment (6 papers), Child and Adolescent Psychosocial and Emotional Development (5 papers), Impact of Technology on Adolescents (5 papers), Anxiety, Depression, Psychometrics, Treatment, Cognitive Processes (4 papers), Mental Health Research Topics (4 papers), COVID-19 and Mental Health (4 papers), Posttraumatic Stress Disorder Research (3 papers) and Food Quality and Safety Studies (3 papers). The work is most often cited by research in Experimental and Cognitive Psychology (63 citations), Biological Psychiatry (11 citations), Clinical Psychology (75 citations), Health Informatics (5 citations) and Applied Psychology (15 citations). Bin‐Na Kim has collaborated with scholars based in South Korea, United States and Ethiopia. Frequent co-authors include Hyo Shin Kang, Seok‐Man Kwon, Jieun E. Kim, Sujung J. Yoon, Jaeuk Hwang, Jooyeon Jamie Im, Jeongwon Yang, Ji‐Hae Kim, Dongsoo Lee and Hong Jin Jeon. Their work appears in journals such as Journal of Affective Disorders, Frontiers in Psychology, Cyberpsychology Behavior and Social Networking, Psychiatry Research and Addictive Behaviors.

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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