Bin‐Na Kim

509 citations
42 papers · 347 · h-index 11

Impact in

Papers in

Bin‐Na Kim

37 papers receiving 330 citations

Peers

Bin‐Na Kim
Comparison fields: 5 of 96
  • Biological Psychiatry 11
  • Experimental and Cognitive Psychology 55
  • Health Informatics 5
  • Clinical Psychology 69
  • Food Science 48
Replace Varsha D. Badal with:
Varsha D. Badal United States
Zhenghai Sun China
Shin Park Australia
Amy Hart United States
Olga Raz Israel
Sofia Bouhlal United States
Lisa Robinson United States
Jessica King United States
Trent Gaugler United States
Bin‐Na Kim relative to Varsha D. Badal United States Varsha D. Badal's profile →
Citations per field
00.5×10×15×
Varsha D. Badal · 1×
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 42 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201688
2 201627
3 201417
4 202116
5 201416
6 202114
7 202112
8
Deep learning-based diagnosis of lung cancer using a nationwide respiratory cytology image set: improving accuracy and inter-observer variability.
202312
9 201911
10 201710
11 201710
12 201210
13 20119
14 20208
15 20178
16 20098
17 20237
18 20177
19 20147
20 20177

About Bin‐Na Kim

Bin‐Na Kim is a scholar working on Clinical Psychology, Sociology and Political Science, Experimental and Cognitive Psychology, Psychiatry and Mental health and Ecology, Evolution, Behavior and Systematics, having authored 42 papers that have together received 347 indexed citations. Recurring topics across this work include Bipolar Disorder and Treatment (6 papers), Impact of Technology on Adolescents (5 papers), Child and Adolescent Psychosocial and Emotional Development (5 papers), COVID-19 and Mental Health (4 papers), Anxiety, Depression, Psychometrics, Treatment, Cognitive Processes (4 papers), Mental Health Research Topics (4 papers), Food Quality and Safety Studies (3 papers) and Posttraumatic Stress Disorder Research (3 papers). The work is most often cited by research in Biological Psychiatry (11 citations), Experimental and Cognitive Psychology (55 citations), Health Informatics (5 citations), Clinical Psychology (69 citations) and Food Science (48 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, Jaeuk Hwang, Sujung Yoon, Jooyeon Jamie Im, Jeongwon Yang, Ji‐Hae Kim, Eun‐Ho Lee and Hong Jin Jeon. Their work appears in journals such as Journal of Affective Disorders, Cyberpsychology Behavior and Social Networking, Frontiers in Psychology, Virtual Reality and PLoS ONE.

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.

Explore authors with similar magnitude of impact