Tingjie Guo

1.1k total citations · 1 hit paper
24 papers, 682 citations indexed

About

Tingjie Guo is a scholar working on Epidemiology, Pharmacology and Infectious Diseases. According to data from OpenAlex, Tingjie Guo has authored 24 papers receiving a total of 682 indexed citations (citations by other indexed papers that have themselves been cited), including 16 papers in Epidemiology, 10 papers in Pharmacology and 8 papers in Infectious Diseases. Recurrent topics in Tingjie Guo's work include Antibiotics Pharmacokinetics and Efficacy (10 papers), Sepsis Diagnosis and Treatment (9 papers) and Tuberculosis Research and Epidemiology (4 papers). Tingjie Guo is often cited by papers focused on Antibiotics Pharmacokinetics and Efficacy (10 papers), Sepsis Diagnosis and Treatment (9 papers) and Tuberculosis Research and Epidemiology (4 papers). Tingjie Guo collaborates with scholars based in Netherlands, South Africa and United Kingdom. Tingjie Guo's co-authors include Armand R. J. Girbes, Paul Elbers, Lucas M. Fleuren, Luca F. Roggeveen, Patrick Thoral, Eleonora L. Swart, Thomas Klausch, Mark Hoogendoorn, Charlotte Zwager and Linda Schoonmade and has published in prestigious journals such as Antimicrobial Agents and Chemotherapy, Pharmaceutical Research and Clinical Pharmacology & Therapeutics.

In The Last Decade

Tingjie Guo

21 papers receiving 670 citations

Hit Papers

Machine learning for the prediction of sepsis: a systemat... 2020 2026 2022 2024 2020 100 200 300 400

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Tingjie Guo Netherlands 11 329 190 123 86 67 24 682
Luca F. Roggeveen Netherlands 9 309 0.9× 192 1.0× 114 0.9× 74 0.9× 66 1.0× 14 612
Lucas M. Fleuren Netherlands 11 345 1.0× 217 1.1× 113 0.9× 78 0.9× 81 1.2× 22 708
Patrick Thoral Netherlands 15 447 1.4× 351 1.8× 86 0.7× 134 1.6× 125 1.9× 37 966
Cara O’Brien United States 14 538 1.6× 233 1.2× 29 0.2× 143 1.7× 48 0.7× 20 1.2k
Gabriel Wardi United States 17 370 1.1× 184 1.0× 21 0.2× 146 1.7× 57 0.9× 75 779
H.M. Giannini United States 4 194 0.6× 164 0.9× 34 0.3× 44 0.5× 29 0.4× 8 340
Janne Cadamuro Austria 26 150 0.5× 63 0.3× 30 0.2× 230 2.7× 83 1.2× 115 2.0k
Rabi Yacoub United States 23 233 0.7× 146 0.8× 40 0.3× 203 2.4× 106 1.6× 46 1.6k
Jens Schierbeck Denmark 10 174 0.5× 112 0.6× 32 0.3× 61 0.7× 33 0.5× 24 502
Thomas Jack Germany 18 234 0.7× 56 0.3× 48 0.4× 248 2.9× 37 0.6× 51 986

Countries citing papers authored by Tingjie Guo

Since Specialization
Citations

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

Fields of papers citing papers by Tingjie Guo

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Tingjie Guo

This figure shows the co-authorship network connecting the top 25 collaborators of Tingjie Guo. A scholar is included among the top collaborators of Tingjie Guo 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 Tingjie Guo. Tingjie Guo 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.
Roggeveen, Luca F., et al.. (2025). Cost-effectiveness of data driven personalised antibiotic dosing in critically ill patients with sepsis or septic shock. Journal of Clinical Monitoring and Computing. 39(5). 937–946.
2.
Manson, Martijn L., et al.. (2025). Revisiting Acyclovir Dosing for Adult Viral Encephalitis Using a Full Bayesian LeiCNS PBPK Modeling Approach. Clinical Pharmacokinetics. 64(9). 1413–1423.
3.
Guo, Tingjie, et al.. (2024). Generation of realistic virtual adult populations using a model-based copula approach. Journal of Pharmacokinetics and Pharmacodynamics. 51(6). 735–746. 2 indexed citations
4.
Graaf, Piet H. van der, et al.. (2024). Predictions of Bedaquiline Central Nervous System Exposure in Patients with Tuberculosis Meningitis Using Physiologically based Pharmacokinetic Modeling. Clinical Pharmacokinetics. 63(5). 657–668. 9 indexed citations
5.
Manson, Martijn L., et al.. (2024). CNS Viral Infections—What to Consider for Improving Drug Treatment: A Plea for Using Mathematical Modeling Approaches. CNS Drugs. 38(5). 349–373. 6 indexed citations
7.
Guo, Tingjie, et al.. (2023). Virtual Patient Simulation Using Copula Modeling. Clinical Pharmacology & Therapeutics. 115(4). 795–804. 7 indexed citations
9.
Guo, Tingjie, et al.. (2023). Model‐based dose optimization framework for bedaquiline, pretomanid and linezolid for the treatment of drug‐resistant tuberculosis. British Journal of Clinical Pharmacology. 90(2). 463–474. 4 indexed citations
10.
Guo, Tingjie, et al.. (2022). Quantitative Systems Pharmacology Modeling Framework of Autophagy in Tuberculosis: Application to Adjunctive Metformin Host-Directed Therapy. Antimicrobial Agents and Chemotherapy. 66(8). e0036622–e0036622. 1 indexed citations
11.
12.
Guo, Tingjie, Alan Abdulla, Birgit C. P. Koch, et al.. (2022). Pooled Population Pharmacokinetic Analysis for Exploring Ciprofloxacin Pharmacokinetic Variability in Intensive Care Patients. Clinical Pharmacokinetics. 61(6). 869–879. 4 indexed citations
13.
Tuinman, Pieter R., Tingjie Guo, Nicole P. Juffermans, et al.. (2021). Between-trial heterogeneity in ARDS research. Intensive Care Medicine. 47(4). 422–434. 15 indexed citations
14.
Guo, Tingjie, et al.. (2021). Identification of high‐dimensional omics‐derived predictors for tumor growth dynamics using machine learning and pharmacometric modeling. CPT Pharmacometrics & Systems Pharmacology. 10(4). 350–361. 4 indexed citations
15.
Fleuren, Lucas M., Thomas Klausch, Charlotte Zwager, et al.. (2020). Machine learning for the prediction of sepsis: a systematic review and meta-analysis of diagnostic test accuracy. Intensive Care Medicine. 46(3). 383–400. 414 indexed citations breakdown →
16.
Guo, Tingjie, Reinier M. van Hest, Luca F. Roggeveen, et al.. (2020). Optimizing Predictive Performance of Bayesian Forecasting for Vancomycin Concentration in Intensive Care Patients. Pharmaceutical Research. 37(9). 171–171. 13 indexed citations
17.
Roggeveen, Luca F., Tingjie Guo, Ronald H. Driessen, et al.. (2020). Right Dose, Right Now: Development of AutoKinetics for Real Time Model Informed Precision Antibiotic Dosing Decision Support at the Bedside of Critically Ill Patients. Frontiers in Pharmacology. 11. 646–646. 21 indexed citations
18.
Roggeveen, Luca F., Tingjie Guo, Lucas M. Fleuren, et al.. (2020). Transatlantic transferability of a new reinforcement learning model for optimizing haemodynamic treatment for critically ill patients with sepsis. Artificial Intelligence in Medicine. 112. 102003–102003. 23 indexed citations
19.
Fleuren, Lucas M., Luca F. Roggeveen, Tingjie Guo, et al.. (2019). Clinically relevant pharmacokinetic knowledge on antibiotic dosing among intensive care professionals is insufficient: a cross-sectional study. Critical Care. 23(1). 185–185. 14 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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