Gee Young Suh

12.8k total citations
360 papers, 7.6k citations indexed

About

Gee Young Suh is a scholar working on Pulmonary and Respiratory Medicine, Epidemiology and Surgery. According to data from OpenAlex, Gee Young Suh has authored 360 papers receiving a total of 7.6k indexed citations (citations by other indexed papers that have themselves been cited), including 154 papers in Pulmonary and Respiratory Medicine, 146 papers in Epidemiology and 96 papers in Surgery. Recurrent topics in Gee Young Suh's work include Sepsis Diagnosis and Treatment (74 papers), Respiratory Support and Mechanisms (57 papers) and Cardiac Arrest and Resuscitation (48 papers). Gee Young Suh is often cited by papers focused on Sepsis Diagnosis and Treatment (74 papers), Respiratory Support and Mechanisms (57 papers) and Cardiac Arrest and Resuscitation (48 papers). Gee Young Suh collaborates with scholars based in South Korea, United States and Canada. Gee Young Suh's co-authors include Kyeongman Jeon, O Jung Kwon, Man Pyo Chung, Hojoong Kim, Won‐Jung Koh, Chi Ryang Chung, Jeong Hoon Yang, Sang‐Won Um, Kyung Soo Lee and Joungho Han and has published in prestigious journals such as SHILAP Revista de lepidopterología, The Journal of Immunology and Journal of the American College of Cardiology.

In The Last Decade

Gee Young Suh

337 papers receiving 7.5k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Gee Young Suh South Korea 45 2.9k 2.7k 1.7k 1.3k 1.1k 360 7.6k
Stefan Kluge Germany 45 2.2k 0.8× 2.6k 1.0× 1.6k 0.9× 1.5k 1.1× 1.3k 1.2× 353 8.8k
Younsuck Koh South Korea 45 2.6k 0.9× 4.3k 1.6× 1.2k 0.7× 1.3k 0.9× 1.3k 1.1× 322 9.3k
Stephen O. Heard United States 38 2.6k 0.9× 2.5k 0.9× 2.4k 1.4× 1.5k 1.1× 1.1k 1.0× 133 11.8k
Kyeongman Jeon South Korea 47 5.4k 1.9× 2.1k 0.8× 1.9k 1.1× 3.5k 2.6× 964 0.9× 359 8.8k
Michael Joannidis Austria 51 2.1k 0.7× 2.5k 0.9× 2.1k 1.2× 770 0.6× 1.2k 1.1× 256 9.9k
Jean‐Paul Mira France 40 2.0k 0.7× 1.4k 0.5× 766 0.4× 785 0.6× 1.5k 1.4× 116 5.9k
Michaël Darmon France 56 3.5k 1.2× 2.8k 1.0× 1.3k 0.7× 1.3k 1.0× 1.2k 1.1× 234 10.3k
Frédéric Pène France 46 2.2k 0.8× 1.2k 0.4× 751 0.4× 716 0.5× 1.5k 1.3× 231 6.7k
Christophe Adrie France 57 3.0k 1.0× 1.8k 0.7× 1.0k 0.6× 686 0.5× 2.3k 2.0× 112 9.0k
Gernot Marx Germany 46 1.4k 0.5× 1.2k 0.5× 1.8k 1.0× 821 0.6× 644 0.6× 297 6.7k

Countries citing papers authored by Gee Young Suh

Since Specialization
Citations

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

Fields of papers citing papers by Gee Young Suh

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Gee Young Suh. 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 Gee Young Suh. The network helps show where Gee Young Suh may publish in the future.

Co-authorship network of co-authors of Gee Young Suh

This figure shows the co-authorship network connecting the top 25 collaborators of Gee Young Suh. A scholar is included among the top collaborators of Gee Young Suh 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 Gee Young Suh. Gee Young Suh 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.
Kim, Song‐Hee, Ryoung‐Eun Ko, Gee Young Suh, et al.. (2025). Simulating the effects of reducing transfer latency from the intensive care unit on intensive care unit bed utilization in a Korean Tertiary Hospital. Acute and Critical Care. 40(1). 18–28.
2.
Sim, Jae Kyeom, Sang‐Min Lee, Hyung Koo Kang, et al.. (2024). Association between mechanical power and intensive care unit mortality in Korean patients under pressure-controlled ventilation. Acute and Critical Care. 39(1). 91–99. 3 indexed citations
3.
Chung, Chi Ryang, et al.. (2024). Epinephrine-induced lactic acidosis during the management of anaphylactic shock: a case report. Clinical and Experimental Emergency Medicine. 12(4). 400–404.
4.
Ahn, Chiwon, et al.. (2024). Comparison of Early and Late Norepinephrine Administration in Patients With Septic Shock. CHEST Journal. 166(6). 1417–1430. 5 indexed citations
5.
Kim, Hyung‐Jun, Dong Kyu Oh, Sung Yoon Lim, et al.. (2023). Antibiogram of Multidrug-Resistant Bacteria Based on Sepsis Onset Location in Korea: A Multicenter Cohort Study. Journal of Korean Medical Science. 38(10). e75–e75. 6 indexed citations
6.
Ko, Ryoung‐Eun, et al.. (2023). Deep Learning-Based Early Warning Score for Predicting Clinical Deterioration in General Ward Cancer Patients. Cancers. 15(21). 5145–5145. 1 indexed citations
7.
8.
Kim, Youngha, Nayeon Kim, Danbee Kang, et al.. (2021). Patient-Reported Outcomes Measurement Information System: Translation and Linguistic Validation of Six Profile Domains for Korean Adults. Journal of Korean Medical Science. 36(33). e212–e212. 3 indexed citations
9.
Park, Jong Eun, Tae Gun Shin, Ik Joon Jo, et al.. (2020). Impact of Vitamin C and Thiamine Administration on Delirium-Free Days in Patients with Septic Shock. Journal of Clinical Medicine. 9(1). 193–193. 17 indexed citations
10.
Ko, Ryoung‐Eun, Hyun Lee, Jin Hee Jung, et al.. (2019). Simple functional assessment at hospital discharge can predict long-term outcomes of ICU survivors. PLoS ONE. 14(4). e0214602–e0214602.
11.
Lee, Mi Suk, Jee Youn Oh, Cheol‐In Kang, et al.. (2018). Guideline for Antibiotic Use in Adults with Community-acquired Pneumonia. Infection and Chemotherapy. 50(2). 160–160. 42 indexed citations
12.
Lee, Seonmin, Kiichi Nakahira, Jesmond Dalli, et al.. (2017). NLRP3 Inflammasome Deficiency Protects Against Microbial Sepsis Via Increased Lipoxin B4 Synthesis. American Journal of Respiratory and Critical Care Medicine. 196(6). 713–726. 131 indexed citations
13.
Yang, Jeong Hoon, et al.. (2017). Refractory Ventricular Arrhythmia Induced by Aconite Intoxication and Its Treatment with Extracorporeal Cardiopulmonary Resuscitation. SHILAP Revista de lepidopterología. 32(2). 228–230. 3 indexed citations
14.
15.
Um, Sang‐Won, Hong Kwan Kim, Sin‐Ho Jung, et al.. (2015). Endobronchial Ultrasound versus Mediastinoscopy for Mediastinal Nodal Staging of Non–Small-Cell Lung Cancer. Journal of Thoracic Oncology. 10(2). 331–337. 142 indexed citations
16.
Jeong, Byeong‐Ho, Hongseok Yoo, Won‐Jung Koh, et al.. (2013). Comparison of Severe Healthcare-Associated Pneumonia with Severe Community-Acquired Pneumonia. Lung. 192(2). 313–320. 9 indexed citations
17.
Park, Hye Kyeong, Kyeongman Jeon, Won‐Jung Koh, et al.. (2012). The role of pleural fluid MAGE RT‐nested PCR in the diagnosis of malignant pleural effusion. Thoracic Cancer. 3(4). 320–325. 2 indexed citations
18.
Kang, Mun Ju, Tae Gun Shin, Ik Joon Jo, et al.. (2012). Factors Influencing Compliance With Early Resuscitation Bundle in the Management of Severe Sepsis and Septic Shock. Shock. 38(5). 474–479. 45 indexed citations
19.
Joung, Mi Kyong, Jeong-A Lee, Soo‐youn Moon, et al.. (2011). Impact of de-escalation therapy on clinical outcomes for intensive care unit-acquired pneumonia. Critical Care. 15(2). R79–R79. 68 indexed citations
20.
Koh, Won‐Jung, O Jung Kwon, Gee Young Suh, et al.. (2004). Mycobacterium avium Complex (MAC) 폐질환의 치료성적. Tuberculosis & respiratory diseases. 57(3). 234–241. 4 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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