Ying P. Tabak

5.4k total citations · 3 hit papers
67 papers, 3.9k citations indexed

About

Ying P. Tabak is a scholar working on Epidemiology, Infectious Diseases and Clinical Biochemistry. According to data from OpenAlex, Ying P. Tabak has authored 67 papers receiving a total of 3.9k indexed citations (citations by other indexed papers that have themselves been cited), including 25 papers in Epidemiology, 16 papers in Infectious Diseases and 11 papers in Clinical Biochemistry. Recurrent topics in Ying P. Tabak's work include Antibiotic Use and Resistance (11 papers), Bacterial Identification and Susceptibility Testing (11 papers) and Emergency and Acute Care Studies (10 papers). Ying P. Tabak is often cited by papers focused on Antibiotic Use and Resistance (11 papers), Bacterial Identification and Susceptibility Testing (11 papers) and Emergency and Acute Care Studies (10 papers). Ying P. Tabak collaborates with scholars based in United States, Australia and Vietnam. Ying P. Tabak's co-authors include Xiaowu Sun, Vikas Gupta, Richard S. Johannes, Andrew F. Shorr, R.S. Johannes, Marin H. Kollef, Larry Z. Liu, Peter A. Banks, Darwin L. Conwell and Bing Wu and has published in prestigious journals such as Gastroenterology, PLoS ONE and Diabetes Care.

In The Last Decade

Ying P. Tabak

63 papers receiving 3.8k citations

Hit Papers

Epidemiology and Outcomes of Health-care–Associated Pneum... 2005 2026 2012 2019 2005 2008 2011 200 400 600

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Ying P. Tabak United States 28 1.4k 1.1k 787 695 568 67 3.9k
Melissa Saul United States 40 1.3k 1.0× 956 0.9× 768 1.0× 496 0.7× 265 0.5× 145 5.5k
Mary Andrus United States 6 2.2k 1.6× 1.4k 1.3× 887 1.1× 1.5k 2.1× 430 0.8× 8 5.7k
Scott A. Flanders United States 30 2.3k 1.7× 603 0.6× 907 1.2× 758 1.1× 544 1.0× 85 5.4k
Olivier Mimoz France 40 1.5k 1.1× 1.5k 1.4× 538 0.7× 1.0k 1.5× 595 1.0× 189 5.6k
Pedro Póvoa Portugal 39 3.0k 2.1× 696 0.6× 668 0.8× 1.5k 2.2× 416 0.7× 204 5.7k
Keith M. Olsen United States 29 1.2k 0.9× 2.2k 2.0× 639 0.8× 1.2k 1.8× 378 0.7× 107 5.5k
Bin Du China 35 2.0k 1.4× 1.0k 0.9× 1.2k 1.6× 1.5k 2.1× 743 1.3× 177 6.1k
Andrew Udy Australia 38 2.6k 1.9× 789 0.7× 905 1.1× 687 1.0× 891 1.6× 215 6.5k
Carole Schwebel France 38 1.8k 1.3× 572 0.5× 607 0.8× 1.4k 2.0× 510 0.9× 124 4.5k
Soumitra R. Eachempati United States 33 1.2k 0.9× 2.0k 1.8× 410 0.5× 571 0.8× 1.6k 2.8× 98 4.5k

Countries citing papers authored by Ying P. Tabak

Since Specialization
Citations

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

Fields of papers citing papers by Ying P. Tabak

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ying P. Tabak. 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 Ying P. Tabak. The network helps show where Ying P. Tabak may publish in the future.

Co-authorship network of co-authors of Ying P. Tabak

This figure shows the co-authorship network connecting the top 25 collaborators of Ying P. Tabak. A scholar is included among the top collaborators of Ying P. Tabak 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 Ying P. Tabak. Ying P. Tabak 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.
Tabak, Ying P., et al.. (2020). Attributable burden in patients with carbapenem-nonsusceptible gram-negative respiratory infections. PLoS ONE. 15(2). e0229393–e0229393. 11 indexed citations
3.
Ridgway, Jessica P., Xiaowu Sun, Ying P. Tabak, Richard S. Johannes, & Ari Robicsek. (2016). Performance characteristics and associated outcomes for an automated surveillance tool for bloodstream infection. American Journal of Infection Control. 44(5). 567–571. 19 indexed citations
4.
Tabak, Ying P., Richard S. Johannes, Xiaowu Sun, Carlos M. Nuñez, & L. Clifford McDonald. (2015). Predicting the Risk for Hospital-Onset Clostridium difficile Infection (HO-CDI) at the Time of Inpatient Admission: HO-CDI Risk Score. Infection Control and Hospital Epidemiology. 36(6). 695–701. 27 indexed citations
5.
Tabak, Ying P., William R. Jarvis, Xiaowu Sun, Cynthia T. Crosby, & Richard S. Johannes. (2014). Meta-analysis on central line–associated bloodstream infections associated with a needleless intravenous connector with a new engineering design. American Journal of Infection Control. 42(12). 1278–1284. 23 indexed citations
7.
Tabak, Ying P., Xiaowu Sun, Carlos M. Nuñez, & Richard S. Johannes. (2013). Using electronic health record data to develop inpatient mortality predictive model: Acute Laboratory Risk of Mortality Score (ALaRMS). Journal of the American Medical Informatics Association. 21(3). 455–463. 85 indexed citations
9.
Shorr, Andrew F., Ying P. Tabak, Richard S. Johannes, et al.. (2011). Burden of Sodium Abnormalities in Patients Hospitalized for Heart Failure. Congestive Heart Failure. 17(1). 1–7. 37 indexed citations
10.
Shorr, Andrew F., Marya D. Zilberberg, Xiaowu Sun, et al.. (2011). Severe acute hypertension among inpatients admitted from the emergency department. Journal of Hospital Medicine. 7(3). 203–210. 10 indexed citations
11.
Saltzman, John R., Ying P. Tabak, Brian Hyett, et al.. (2011). A simple risk score accurately predicts in-hospital mortality, length of stay, and cost in acute upper GI bleeding. Gastrointestinal Endoscopy. 74(6). 1215–1224. 338 indexed citations breakdown →
13.
Tabak, Ying P.. (2009). Economic Burden of Nosocomial Infection on Payers and Providers: Analysis of 272,143 Admissions in 2007. 1 indexed citations
14.
Tabak, Ying P., Xiaowu Sun, Richard S. Johannes, Vikas Gupta, & Andrew F. Shorr. (2009). Mortality and Need for Mechanical Ventilation in Acute Exacerbations of Chronic Obstructive Pulmonary Disease. Archives of Internal Medicine. 169(17). 1595–602. 88 indexed citations
15.
Shorr, Andrew F., Vikas Gupta, Xiaowu Sun, et al.. (2009). Burden of early-onset candidemia: Analysis of culture-positive bloodstream infections from a large U.S. database*. Critical Care Medicine. 37(9). 2519–2526. 50 indexed citations
16.
Wu, Bing, R.S. Johannes, Xiaowu Sun, et al.. (2008). The early prediction of mortality in acute pancreatitis: a large population-based study. Gut. 57(12). 1698–1703. 576 indexed citations breakdown →
17.
Shorr, Andrew F., et al.. (2006). Morbidity and cost burden of methicillin-resistant Staphylococcus aureus in early onset ventilator-associated pneumonia. Critical Care. 10(3). R97–R97. 130 indexed citations
18.
Kollef, Marin H., Andrew F. Shorr, Ying P. Tabak, et al.. (2005). Epidemiology and Outcomes of Health-care–Associated Pneumonia. CHEST Journal. 128(6). 3854–3862. 721 indexed citations breakdown →
19.
Tabak, Ying P. & R.S. Johannes. (2004). Using Automated Clinical Data on Admission to Predict Mortality of Patients with Pneumonia. CHEST Journal. 126(4). 738S–738S. 1 indexed citations
20.
Shorr, Andrew F., Ying P. Tabak, Vikas Gupta, et al.. (2004). The Burden of Methicillin Resistant Staphylococcus aureus in Ventilator-Associated Pneumonia. CHEST Journal. 126(4). 716S–716S.

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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