Hojae Lee

802 total citations
42 papers, 552 citations indexed

About

Hojae Lee is a scholar working on Aerospace Engineering, Mechanical Engineering and Physiology. According to data from OpenAlex, Hojae Lee has authored 42 papers receiving a total of 552 indexed citations (citations by other indexed papers that have themselves been cited), including 13 papers in Aerospace Engineering, 10 papers in Mechanical Engineering and 6 papers in Physiology. Recurrent topics in Hojae Lee's work include High-Temperature Coating Behaviors (13 papers), Advanced ceramic materials synthesis (5 papers) and Materials Engineering and Processing (4 papers). Hojae Lee is often cited by papers focused on High-Temperature Coating Behaviors (13 papers), Advanced ceramic materials synthesis (5 papers) and Materials Engineering and Processing (4 papers). Hojae Lee collaborates with scholars based in South Korea, United Kingdom and Spain. Hojae Lee's co-authors include Jin-Seok Choi, Kwang-Wook Ko, Kyung‐Seok Ko, Ho-Jung Shin, S. Lee, Dong Keon Yon, Lee Smith, Ai Koyanagi, Masoud Rahmati and Jaeyu Park and has published in prestigious journals such as Scientific Reports, Journal of Allergy and Clinical Immunology and Journal of Investigative Dermatology.

In The Last Decade

Hojae Lee

38 papers receiving 535 citations

Peers

Hojae Lee
David Drewry United States
Ali Ceylan Türkiye
F. Hoffmann Germany
Fengyun Yu China
Parimal J. Patel United States
Hyoung Keun Park South Korea
S. Diouf Senegal
Anneke C. Bush United States
Shiyan Chen China
Chih‐Hsiang Chang Taiwan
David Drewry United States
Hojae Lee
Citations per year, relative to Hojae Lee Hojae Lee (= 1×) peers David Drewry

Countries citing papers authored by Hojae Lee

Since Specialization
Citations

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

Fields of papers citing papers by Hojae Lee

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Hojae Lee

This figure shows the co-authorship network connecting the top 25 collaborators of Hojae Lee. A scholar is included among the top collaborators of Hojae Lee 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 Hojae Lee. Hojae Lee 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
1.
Lee, Jae Eun, Soeun Kim, Hojae Lee, et al.. (2025). Long-term trends in the prevalence of cardiovascular-kidney-metabolic syndrome in South Korea, 2011–2021: a representative longitudinal serial study. The Lancet Regional Health - Western Pacific. 55. 101474–101474. 6 indexed citations
2.
Kim, Soeun, Hojae Lee, Hyeon Jin Kim, et al.. (2025). Machine Learning–Based Prediction of Substance Use in Adolescents in Three Independent Worldwide Cohorts: Algorithm Development and Validation Study. Journal of Medical Internet Research. 27. e62805–e62805.
3.
Lee, Jun Hyuk, Myeongcheol Lee, Hojae Lee, et al.. (2024). National trends in sexual intercourse and usage of contraception among Korean adolescents. World Journal of Pediatrics. 20(9). 935–948. 7 indexed citations
4.
Lee, Hojae, Myeongcheol Lee, Jaeyu Park, et al.. (2024). Prediction model for cardiovascular disease in patients with diabetes using machine learning derived and validated in two independent Korean cohorts. Scientific Reports. 14(1). 14966–14966. 12 indexed citations
5.
Lee, Hojae, Jaeyu Park, Sun Young Kim, et al.. (2024). Machine Learning–Based Prediction of Neurodegenerative Disease in Patients With Type 2 Diabetes by Derivation and Validation in 2 Independent Korean Cohorts: Model Development and Validation Study. Journal of Medical Internet Research. 26. e56922–e56922. 2 indexed citations
6.
Lee, Hojae, Jaeyu Park, Hyeri Lee, et al.. (2024). Machine Learning–Based Prediction of Suicidality in Adolescents With Allergic Rhinitis: Derivation and Validation in 2 Independent Nationwide Cohorts. Journal of Medical Internet Research. 26. e51473–e51473. 23 indexed citations
7.
Lee, Hojae, Jiseung Kang, Hyeon Jin Kim, et al.. (2024). Machine Learning–Based Prediction of Suicidal Thinking in Adolescents by Derivation and Validation in 3 Independent Worldwide Cohorts: Algorithm Development and Validation Study. Journal of Medical Internet Research. 26. e55913–e55913. 17 indexed citations
8.
Lee, Myeongcheol, Jaeyu Park, Ha-Yeon Lee, et al.. (2024). Temporal changes in smoking prevalence among adolescents across 23 countries. Acta Paediatrica. 114(6). 1189–1201. 1 indexed citations
9.
Lee, Hojae, Jaeyu Park, Myeongcheol Lee, et al.. (2024). National Trends in Allergic Rhinitis and Chronic Rhinosinusitis and COVID-19 Pandemic-Related Factors in South Korea, from 1998 to 2021. International Archives of Allergy and Immunology. 185(4). 355–361. 9 indexed citations
10.
Park, Jaeyu, Myeongcheol Lee, Sun Young Kim, et al.. (2024). National prevalence of smoking among adolescents at tobacco tax increase and COVID-19 pandemic in South Korea, 2005–2022. Scientific Reports. 14(1). 7823–7823. 9 indexed citations
11.
Kim, Hye Jun, Jaeyu Park, Hojae Lee, et al.. (2024). Risks of cutaneous immune‐related adverse events in long COVID: Multinational cohort studies in South Korea, Japan, and the UK. Journal of Medical Virology. 96(6). e29740–e29740. 7 indexed citations
12.
13.
Kang, Jiseung, Jaeyu Park, Hojae Lee, et al.. (2023). National trends in depression and suicide attempts and COVID-19 pandemic-related factors, 1998–2021: A nationwide study in South Korea. Asian Journal of Psychiatry. 88. 103727–103727. 19 indexed citations
14.
Kwon, Rosie, Hojae Lee, Seung Won Lee, et al.. (2023). Viral load dynamics and shedding kinetics of mpox infection: a systematic review and meta-analysis. Journal of Travel Medicine. 30(5). 23 indexed citations
15.
Oh, Jiyeon, Myeongcheol Lee, Hojae Lee, et al.. (2023). Hand and Oral Hygiene Practices of South Korean Adolescents Before and During the COVID-19 Pandemic. JAMA Network Open. 6(12). e2349249–e2349249. 21 indexed citations
16.
Lee, Myeongcheol, Hojae Lee, Jaeyu Park, et al.. (2023). Trends in hypertension prevalence, awareness, treatment, and control in South Korea, 1998–2021: a nationally representative serial study. Scientific Reports. 13(1). 125–128. 15 indexed citations
17.
Park, Jaeyu, Myeongcheol Lee, Hojae Lee, et al.. (2023). National trends in rheumatoid arthritis and osteoarthritis prevalence in South Korea, 1998–2021. Scientific Reports. 13(1). 19528–19528. 9 indexed citations
18.
19.
Lee, Hojae, et al.. (2017). 033 Clinical characteristics according to therapeutic efficacy of cyclosporine or methotrexate in patients with psoriasis vulgaris. Journal of Investigative Dermatology. 137(10). S198–S198. 1 indexed citations
20.
Lee, Jeong-Jae, et al.. (2003). A Study on the Longevity Index and the Criteria of Longevity in Rural Area for Aged Society. Journal of Korean Society of Rural Planning. 9(3). 35–39. 3 indexed citations

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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