Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies
if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the
same subfield and year (this is the minimum needed to enter the top 1%, not the average
within it), or reaches the top citation threshold in at least one of its specific research
topics.
Network meta-analysis: application and practice using Stata
2017437 citationsSung Ryul Shim, Byung‐Ho Yoon et al.Epidemiology and Healthprofile →
Peers — A (Enhanced Table)
Peers by citation overlap · career bar shows stage (early→late)
cites ·
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This map shows the geographic impact of Jong‐Myon Bae'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 Jong‐Myon Bae with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jong‐Myon Bae more than expected).
This network shows the impact of papers produced by Jong‐Myon Bae. 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 Jong‐Myon Bae. The network helps show where Jong‐Myon Bae may publish in the future.
Co-authorship network of co-authors of Jong‐Myon Bae
This figure shows the co-authorship network connecting the top 25 collaborators of Jong‐Myon Bae.
A scholar is included among the top collaborators of Jong‐Myon Bae 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 Jong‐Myon Bae. Jong‐Myon Bae is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Bae, Jong‐Myon. (2019). Differences of clinical manifestation of severe fever with thrombocytopenia syndrome between Korean and Chinese patients. Journal of the Korean society of emergency medicine. 30(3). 205–207.1 indexed citations
Shim, Sung Ryul, Byung‐Ho Yoon, In‐Soo Shin, & Jong‐Myon Bae. (2017). Network meta-analysis: application and practice using Stata. Epidemiology and Health. 39. e2017047–e2017047.437 indexed citations breakdown →
7.
Bae, Jong‐Myon, et al.. (2016). Human Mammary Tumor Virus (HMTV) Infection and Risk of Human Breast Cancer: An Adaptive Meta-Analysis for Case-Control Studies. 5(1). 111–117.1 indexed citations
Shim, Sung Ryul, et al.. (2015). Meta-analysis of Diagnostic Tests Accuracy using STATA Software. Journal of Health Informatics. 40(3). 190–199.4 indexed citations
11.
Bae, Jong‐Myon. (2015). The Clinical Prediction Model for Primary Care Physicians. 5(1). 1–6.1 indexed citations
12.
Bae, Jong‐Myon. (2015). Indices for the Responsiveness and Interpretability in Patient-Reported Outcomes. 5(3). 161–166.2 indexed citations
Bae, Jong‐Myon. (2014). On the Benefi ts and Harms of Mammography for Breast Cancer Screening in Korean Women. 4(1). 1–6.7 indexed citations
15.
Kim, Youn Nam, et al.. (2014). Cohort Effects of Female Breast Cancer Incidence in Korea. Journal of Health Informatics. 39(2). 32–43.4 indexed citations
Kim, Dong‐Hyun, Sung‐Woo Park, Moon Gi Choi, et al.. (1999). Incidence and Risk Factors for Diabetes Mellitus in Korean Middle-aged Men: Seoul Cohort DM Follow-up Study. Journal of Preventive Medicine and Public Health. 32(4). 526–537.8 indexed citations
19.
Kim, Dae Sung, Jong‐Myon Bae, Myung‐Hee Shin, et al.. (1998). A Cohort Study of Physical Activity and All Cause Mortality in Middle-aged Men in Seoul. Journal of Preventive Medicine and Public Health. 31(4). 601–614.7 indexed citations
20.
Park, Byung‐Joo, Jong‐Myon Bae, Yoon‐Ok Ahn, & Keun-Young Yoo. (1994). Survey Methods on Cancer Epidemic. Journal of Preventive Medicine and Public Health. 27(3). 411–423.
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.