Nikolay S. Markov

5.1k total citations · 1 hit paper
15 papers, 842 citations indexed

About

Nikolay S. Markov is a scholar working on Critical Care and Intensive Care Medicine, Pulmonary and Respiratory Medicine and Epidemiology. According to data from OpenAlex, Nikolay S. Markov has authored 15 papers receiving a total of 842 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Critical Care and Intensive Care Medicine, 3 papers in Pulmonary and Respiratory Medicine and 3 papers in Epidemiology. Recurrent topics in Nikolay S. Markov's work include Respiratory Support and Mechanisms (3 papers), Nosocomial Infections in ICU (3 papers) and Pneumonia and Respiratory Infections (2 papers). Nikolay S. Markov is often cited by papers focused on Respiratory Support and Mechanisms (3 papers), Nosocomial Infections in ICU (3 papers) and Pneumonia and Respiratory Infections (2 papers). Nikolay S. Markov collaborates with scholars based in United States, Poland and Vietnam. Nikolay S. Markov's co-authors include Catherine A. Gao, Yuan Luo, Frederick M. Howard, Siddhi Ramesh, Emma Dyer, Alexander T. Pearson, Yuliya Politanska, Hiam Abdala‐Valencia, Alexander V. Misharin and G. R. Scott Budinger and has published in prestigious journals such as Journal of Clinical Investigation, Bioinformatics and American Journal of Respiratory and Critical Care Medicine.

In The Last Decade

Nikolay S. Markov

11 papers receiving 822 citations

Hit Papers

1 papers align trajectories

What are hit papers?

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.

Comparing scientific abstracts generated by ChatGPT to real abstracts with detectors and blinded human reviewers

2023 373 citations Catherine A. Gao, Frederick M. Howard et al. npj Digital Medicine profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Nikolay S. Markov United States	8	286	156	156	119	112	15	842
Albert T. Young United States	14	153 0.5×	136 0.9×	154 1.0×	47 0.4×	99 0.9×	27	868
Margaret Pain United States	15	134 0.5×	111 0.7×	147 0.9×	71 0.6×	203 1.8×	31	800
Boris Oskotsky United States	8	41 0.1×	313 2.0×	120 0.8×	76 0.6×	59 0.5×	12	747
Peter Chang United States	16	65 0.2×	140 0.9×	236 1.5×	160 1.3×	707 6.3×	23	1.4k
Julia K. Winkler Germany	16	60 0.2×	102 0.7×	296 1.9×	66 0.6×	218 1.9×	53	1.0k
Nicolas Garcelon France	15	47 0.2×	292 1.9×	176 1.1×	82 0.7×	35 0.3×	84	863
Christopher A. Lovejoy United Kingdom	9	335 1.2×	34 0.2×	238 1.5×	66 0.6×	306 2.7×	14	844
Emma Dyer United States	11	299 1.0×	132 0.8×	190 1.2×	44 0.4×	134 1.2×	23	726
Javin Schefflein United States	10	140 0.5×	33 0.2×	153 1.0×	50 0.4×	220 2.0×	21	742
Brigid Betz‐Stablein Australia	17	23 0.1×	121 0.8×	110 0.7×	32 0.3×	113 1.0×	60	1.0k

Countries citing papers authored by Nikolay S. Markov

Since Specialization

Citations

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

Fields of papers citing papers by Nikolay S. Markov

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Nikolay S. Markov. 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 Nikolay S. Markov. The network helps show where Nikolay S. Markov may publish in the future.

Co-authorship network of co-authors of Nikolay S. Markov

This figure shows the co-authorship network connecting the top 25 collaborators of Nikolay S. Markov. A scholar is included among the top collaborators of Nikolay S. Markov 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 Nikolay S. Markov. Nikolay S. Markov is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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15 of 15 papers shown

Kang, Mengjia, Nikolay S. Markov, Anna Pawlowski, et al.. (2025). Developing and validating machine learning models to predict next-day extubation. Scientific Reports. 15(1). 27552–27552.

Pickens, Chiagozie I., Nikolay S. Markov, Anna Pawlowski, et al.. (2025). Antibiotic de-escalation patterns and outcomes in critically ill patients with suspected pneumonia as informed by bronchoalveolar lavage results. European Journal of Clinical Microbiology & Infectious Diseases. 44(8). 1861–1871.

Gao, Catherine A., Nikolay S. Markov, Chiagozie I. Pickens, et al.. (2025). An Observational Cohort Study of Bronchoalveolar Lavage Fluid Galactomannan and Aspergillus Culture Positivity in Patients Requiring Mechanical Ventilation. Open Forum Infectious Diseases. 12(3). ofaf090–ofaf090.

Markov, Nikolay S., Mengjia Kang, Alok Choudhary, et al.. (2025). Machine Learning to Predict the Onset of Ventilator-associated Pneumonia Using Electronic Health Record Data. American Journal of Respiratory and Critical Care Medicine. 211(Supplement_1). A7723–A7723.

Gao, Catherine A., Nikolay S. Markov, Thomas Stoeger, et al.. (2023). Machine learning links unresolving secondary pneumonia to mortality in patients with severe pneumonia, including COVID-19. Journal of Clinical Investigation. 133(12). 23 indexed citations

Gao, Catherine A., Frederick M. Howard, Nikolay S. Markov, et al.. (2023). Comparing scientific abstracts generated by ChatGPT to real abstracts with detectors and blinded human reviewers. npj Digital Medicine. 6(1). 75–75. 373 indexed citations breakdown →

Villéger, Romain, Randy C. Mifflin, Nikolay S. Markov, et al.. (2022). Loss of alcohol dehydrogenase 1B in cancer-associated fibroblasts: contribution to the increase of tumor-promoting IL-6 in colon cancer. British Journal of Cancer. 128(4). 537–548. 7 indexed citations

Speir, Matthew L, Aparna Bhaduri, Nikolay S. Markov, et al.. (2021). UCSC Cell Browser: visualize your single-cell data. Bioinformatics. 37(23). 4578–4580. 144 indexed citations

Morales‐Nebreda, Luisa, Kathryn A. Helmin, Manuel A. Torres Acosta, et al.. (2021). Aging imparts cell-autonomous dysfunction to regulatory T cells during recovery from influenza pneumonia. JCI Insight. 6(6). 39 indexed citations

10.

Koch, Clarissa M., Andrew D. Prigge, Kishore R. Anekalla, et al.. (2021). Age-related Differences in the Nasal Mucosal Immune Response to SARS-CoV-2. American Journal of Respiratory Cell and Molecular Biology. 66(2). 206–222. 20 indexed citations

11.

Runyan, Constance E., Lynn C. Welch, Emilia Lecuona, et al.. (2020). Impaired phagocytic function in CX3CR1 ⁺ tissue‐resident skeletal muscle macrophages prevents muscle recovery after influenza A virus‐induced pneumonia in old mice. Aging Cell. 19(9). e13180–e13180. 27 indexed citations

12.

Bharat, Ankit, Melissa Querrey, Nikolay S. Markov, et al.. (2020). Lung transplantation for patients with severe COVID-19. Science Translational Medicine. 12(574). 194 indexed citations

13.

Runyan, Constance E., Lynn C. Welch, Emilia Lecuona, et al.. (2020). Impaired Phagocytic Function in CX3CR1 ⁺ Tissue-Resident Skeletal Muscle Macrophages Prevents Muscle Recovery After Influenza A Virus-Induced Pneumonia in Aged Mice. A2970–A2970. 1 indexed citations

14.

Linkov, A. M. & Nikolay S. Markov. (2020). Improved pseudo three-dimensional model for hydraulic fractures under stress contrast. International Journal of Rock Mechanics and Mining Sciences. 130. 104316–104316. 12 indexed citations

15.

Markov, Nikolay S., et al.. (2007). Digitisation and Access to Archival Collections: A Case Study of the Sofia Municipal Government (1878-1879). Elpub digital library. 277–284. 2 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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