Won-Suk Oh

879 total citations
20 papers, 154 citations indexed

About

Won-Suk Oh is a scholar working on Artificial Intelligence, Epidemiology and Nephrology. According to data from OpenAlex, Won-Suk Oh has authored 20 papers receiving a total of 154 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Artificial Intelligence, 7 papers in Epidemiology and 5 papers in Nephrology. Recurrent topics in Won-Suk Oh's work include Machine Learning in Healthcare (8 papers), Sepsis Diagnosis and Treatment (4 papers) and Chronic Kidney Disease and Diabetes (3 papers). Won-Suk Oh is often cited by papers focused on Machine Learning in Healthcare (8 papers), Sepsis Diagnosis and Treatment (4 papers) and Chronic Kidney Disease and Diabetes (3 papers). Won-Suk Oh collaborates with scholars based in United States, Thailand and South Korea. Won-Suk Oh's co-authors include Girish N. Nadkarni, György Simon, M. Regina Castro, Pedro J. Caraballo, Michael Steinbach, Vipin Kumar, Soo Borson, Lili Chan, Kullaya Takkavatakarn and Yang‐Gyun Kim and has published in prestigious journals such as Journal of the American College of Cardiology, Critical Care and Journal of the American Medical Informatics Association.

In The Last Decade

Won-Suk Oh

15 papers receiving 151 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Won-Suk Oh United States 8 73 39 23 22 22 20 154
Chungsoo Kim South Korea 9 42 0.6× 19 0.5× 11 0.5× 24 1.1× 24 1.1× 41 208
Giulia Cogni Italy 7 145 2.0× 179 4.6× 134 5.8× 37 1.7× 44 2.0× 7 412
Ji Cui China 11 44 0.6× 44 1.1× 17 0.7× 60 2.7× 17 0.8× 30 436
Xiaojuan Hu China 9 41 0.6× 35 0.9× 13 0.6× 61 2.8× 12 0.5× 19 363
Bader Aldughayfiq Saudi Arabia 7 76 1.0× 39 1.0× 13 0.6× 15 0.7× 10 0.5× 18 279
Liping Tu China 13 48 0.7× 45 1.2× 17 0.7× 75 3.4× 21 1.0× 45 607
Xuxiang Ma China 8 28 0.4× 24 0.6× 8 0.3× 30 1.4× 14 0.6× 12 280
Anima Singh United States 6 80 1.1× 59 1.5× 4 0.2× 17 0.8× 28 1.3× 7 149
Theofilos Papadopoulos Greece 9 17 0.2× 25 0.6× 10 0.4× 131 6.0× 16 0.7× 14 339
Rohit Joshi United States 7 206 2.8× 57 1.5× 4 0.2× 63 2.9× 89 4.0× 7 310

Countries citing papers authored by Won-Suk Oh

Since Specialization
Citations

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

Fields of papers citing papers by Won-Suk Oh

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Won-Suk Oh. 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 Won-Suk Oh. The network helps show where Won-Suk Oh may publish in the future.

Co-authorship network of co-authors of Won-Suk Oh

This figure shows the co-authorship network connecting the top 25 collaborators of Won-Suk Oh. A scholar is included among the top collaborators of Won-Suk Oh 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 Won-Suk Oh. Won-Suk Oh 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.
Takkavatakarn, Kullaya, Gopi Patel, Won-Suk Oh, et al.. (2025). Electronic clinical decision support system guided blood culture stewardship in emergency departments: response to the national blood culture media shortage. Infection Control and Hospital Epidemiology. 46(6). 650–653.
2.
Oh, Won-Suk, Hernando Gómez, Mayte Suárez‐Fariñas, et al.. (2025). ORAKLE: Optimal Risk prediction for mAke30 in patients with sepsis associated AKI using deep LEarning. Critical Care. 29(1). 212–212.
3.
Takkavatakarn, Kullaya, Won-Suk Oh, Lili Chan, et al.. (2024). Machine learning derived serum creatinine trajectories in acute kidney injury in critically ill patients with sepsis. Critical Care. 28(1). 156–156. 14 indexed citations
4.
Takkavatakarn, Kullaya, et al.. (2023). Machine learning models to predict end-stage kidney disease in chronic kidney disease stage 4. BMC Nephrology. 24(1). 376–376. 8 indexed citations
5.
DiMenna, Fred J., Won-Suk Oh, Ira Hofer, et al.. (2023). Discrepancy between predicted and measured exercise intensity for eliciting the maximal rate of lipid oxidation. Nutrition Metabolism and Cardiovascular Diseases. 33(11). 2189–2198. 1 indexed citations
6.
Oh, Won-Suk & Girish N. Nadkarni. (2023). Federated Learning in Health care Using Structured Medical Data. PubMed. 30(1). 4–16. 30 indexed citations
7.
8.
Oh, Won-Suk, Pushkala Jayaraman, Pranai Tandon, et al.. (2023). A novel method leveraging time series data to improve subphenotyping and application in critically ill patients with COVID-19. Artificial Intelligence in Medicine. 148. 102750–102750. 1 indexed citations
9.
Jiang, Joy X., Lili Chan, Jagat Narula, Won-Suk Oh, & Girish N. Nadkarni. (2023). IMPACT OF VACCINATION ON MAJOR ADVERSE CARDIOVASCULAR EVENTS AMONG PATIENTS WITH COVID-19. Journal of the American College of Cardiology. 81(8). 1684–1684.
10.
Oh, Won-Suk, Minhae Cho, Su Woong Jung, et al.. (2022). High physical activity alleviates the adverse effect of higher sedentary time on the incidence of chronic kidney disease. Journal of Cachexia Sarcopenia and Muscle. 14(1). 622–631. 10 indexed citations
11.
Oh, Won-Suk, Pushkala Jayaraman, Lili Chan, et al.. (2021). OUP accepted manuscript. Journal of the American Medical Informatics Association. 29(3). 489–499. 5 indexed citations
12.
Oh, Won-Suk, Michael Steinbach, M. Regina Castro, et al.. (2021). A Computational Method for Learning Disease Trajectories From Partially Observable EHR Data. IEEE Journal of Biomedical and Health Informatics. 25(7). 2476–2486. 8 indexed citations
13.
Jung, Su Woong, Minhae Cho, Won-Suk Oh, et al.. (2020). Incremental Effect of Aging on Obesity-Related Incident Chronic Kidney Disease in the Korean General Population. Journal of the American Medical Directors Association. 22(8). 1751–1756.e2. 2 indexed citations
14.
Oh, Won-Suk, Michael Steinbach, M. Regina Castro, et al.. (2019). Evaluating the Impact of Data Representation on EHR-Based Analytic Tasks. Studies in health technology and informatics. 264. 288–292. 4 indexed citations
15.
Zeng, Wenjun, et al.. (2017). Personalized long-term prediction of cognitive function: Using sequential assessments to improve model performance. Journal of Biomedical Informatics. 76. 78–86. 5 indexed citations
16.
Oh, Won-Suk, Pranjul Yadav, Vipin Kumar, et al.. (2017). Estimating Disease Onset Time by Modeling Lab Result Trajectories via Bayes Networks. PubMed. 39. 374–379. 1 indexed citations
17.
Oh, Won-Suk, M. Regina Castro, Pedro J. Caraballo, et al.. (2016). Type 2 Diabetes Mellitus Trajectories and Associated Risks. Big Data. 4(1). 25–30. 41 indexed citations
18.
Oh, Won-Suk, et al.. (2015). Feasibility Study of a Machine Learning Approach to Predict Dementia Progression. 450–450. 15 indexed citations
19.
Oh, Won-Suk, et al.. (2014). Divisive Hierarchical Clustering towards Identifying Clinically Significant Pre-Diabetes Subpopulations.. PubMed. 2014. 1815–24. 9 indexed citations
20.

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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