Nikolay S. Markov
- Health Informatics top 0.2%
- Molecular Biology
- Artificial Intelligence top 10%
- Pulmonary and Respiratory Medicine
- Radiology, Nuclear Medicine and Imaging top 10%
- Co-authors
- Catherine A. GaoYuan LuoEmma DyerFrederick M. HowardSiddhi RameshAlexander T. PearsonHiam Abdala‐ValenciaYuliya Politanska
- Topics
- Respiratory Support and Mechanisms (3 papers)Nosocomial Infections in ICU (3 papers)Pneumonia and Respiratory Infections (2 papers)
- Journals
- Journal of Clinical InvestigationBioinformaticsAmerican Journal of Respiratory and Critical Care Medicine
- Partner nations
- United StatesPolandVietnam
In The Last Decade
Nikolay S. Markov
11 papers receiving 822 citations
Hit Papers
Peers
Comparison fields: 5 of 128
- Health Informatics 286
- Molecular Biology 156
- Artificial Intelligence 156
- Pulmonary and Respiratory Medicine 119
- Radiology, Nuclear Medicine and Imaging 112
Countries citing papers authored by Nikolay S. Markov
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
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
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 0 | |
| 3 | 0 | |
| 4 | 0 | |
| 5 | 23 | |
| 6 | Comparing scientific abstracts generated by ChatGPT to real abstracts with detectors and blinded human reviewersbreakdown → | 373 |
| 7 | 7 | |
| 8 | 144 | |
| 9 | 39 | |
| 10 | 20 | |
| 11 | 194 | |
| 12 | 27 | |
| 13 | 1 | |
| 14 | 12 | |
| 15 | Digitisation and Access to Archival Collections: A Case Study of the Sofia Municipal Government (1878-1879) | 2 |
About Nikolay S. Markov
Nikolay S. Markov is a scholar working on Critical Care and Intensive Care Medicine, Health Informatics and Health Information Management, having authored 15 papers that have together received 842 indexed citations. Recurring topics across this work include Respiratory Support and Mechanisms (3 papers), Nosocomial Infections in ICU (3 papers) and Pneumonia and Respiratory Infections (2 papers). The work is most often cited by research in Health Informatics (286 citations), Family Practice (26 citations) and Infectious Diseases (101 citations). Nikolay S. Markov has collaborated with scholars based in United States, Poland and Vietnam. Frequent co-authors include Catherine A. Gao, Yuan Luo, Emma Dyer, Frederick M. Howard, Siddhi Ramesh, Alexander T. Pearson, Hiam Abdala‐Valencia, Yuliya Politanska, Alexander V. Misharin and G. R. Scott Budinger. Their work appears in journals such as Journal of Clinical Investigation, Bioinformatics and American Journal of Respiratory and Critical Care Medicine.
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.