Maxim S. Petrov

13.6k total citations · 3 hit papers
248 papers, 9.2k citations indexed

About

Maxim S. Petrov is a scholar working on Surgery, Oncology and Epidemiology. According to data from OpenAlex, Maxim S. Petrov has authored 248 papers receiving a total of 9.2k indexed citations (citations by other indexed papers that have themselves been cited), including 204 papers in Surgery, 87 papers in Oncology and 80 papers in Epidemiology. Recurrent topics in Maxim S. Petrov's work include Pancreatitis Pathology and Treatment (187 papers), Pancreatic and Hepatic Oncology Research (86 papers) and Liver Disease Diagnosis and Treatment (65 papers). Maxim S. Petrov is often cited by papers focused on Pancreatitis Pathology and Treatment (187 papers), Pancreatic and Hepatic Oncology Research (86 papers) and Liver Disease Diagnosis and Treatment (65 papers). Maxim S. Petrov collaborates with scholars based in New Zealand, United States and Russia. Maxim S. Petrov's co-authors include John A. Windsor, Dhiraj Yadav, Ruma G. Singh, Sayali A. Pendharkar, Anthony R.J. Phillips, Jaelim Cho, Landy M. Wu, Varsha Asrani, Amy Xiao and S. Shanbhag and has published in prestigious journals such as SHILAP Revista de lepidopterología, Gastroenterology and Diabetes Care.

In The Last Decade

Maxim S. Petrov

242 papers receiving 9.0k citations

Hit Papers

Organ Failure and Infecti... 2010 2026 2015 2020 2010 2018 2016 100 200 300 400 500

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Maxim S. Petrov New Zealand 50 7.6k 3.9k 2.3k 1.4k 1.3k 248 9.2k
Tatjana Stojaković Austria 48 2.3k 0.3× 3.2k 0.8× 1.6k 0.7× 879 0.6× 1.3k 1.0× 226 8.2k
Kazuhiro Hanazaki Japan 39 2.7k 0.4× 1.6k 0.4× 930 0.4× 752 0.5× 1.8k 1.4× 421 5.9k
C. S. Pitchumoni United States 34 2.7k 0.4× 1.4k 0.3× 896 0.4× 444 0.3× 535 0.4× 82 4.1k
Claire Bonithon‐Kopp France 41 843 0.1× 1.6k 0.4× 851 0.4× 626 0.4× 1.6k 1.3× 113 5.4k
A.F. Attili Italy 43 3.2k 0.4× 870 0.2× 2.7k 1.2× 210 0.1× 1.3k 1.0× 145 5.9k
Maarten Naesens Belgium 55 3.0k 0.4× 972 0.3× 977 0.4× 214 0.2× 1.3k 1.0× 242 9.0k
Hallvard Holdaas Norway 44 3.5k 0.5× 503 0.1× 513 0.2× 972 0.7× 1.5k 1.2× 215 7.6k
P J Guillou United Kingdom 40 4.8k 0.6× 5.5k 1.4× 771 0.3× 87 0.1× 2.3k 1.8× 122 8.7k
Alberto Lorenzatti Argentina 15 5.8k 0.8× 250 0.1× 1.9k 0.8× 2.3k 1.7× 672 0.5× 29 9.5k
Paolo Muiesan United Kingdom 51 6.4k 0.8× 929 0.2× 1.9k 0.8× 168 0.1× 830 0.6× 295 8.7k

Countries citing papers authored by Maxim S. Petrov

Since Specialization
Citations

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

Fields of papers citing papers by Maxim S. Petrov

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Maxim S. Petrov

This figure shows the co-authorship network connecting the top 25 collaborators of Maxim S. Petrov. A scholar is included among the top collaborators of Maxim S. Petrov 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 Maxim S. Petrov. Maxim S. Petrov 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
2.
Zhang, Yingxin, Yutong Liu, & Maxim S. Petrov. (2025). Relationship of fat in the pancreas with cardiovascular disease: A systematic review and meta‐analysis. Obesity Reviews. 26(7). e13914–e13914. 8 indexed citations
3.
Hamada, Tsuyoshi, et al.. (2025). Intraductal Papillary Mucinous Neoplasm and Pancreatic Cancer: Opportunity Knocks Twice. The American Journal of Gastroenterology. 121(2). 312–321.
4.
Liu, Yutong, et al.. (2025). Relationship of intra‐pancreatic fat deposition with low‐density lipoprotein subfractions and hepatic lipase. Diabetes Obesity and Metabolism. 27(11). 6674–6681. 1 indexed citations
5.
Cho, Jaelim & Maxim S. Petrov. (2024). Epidemiology of post-pancreatitis diabetes mellitus: insights from the COSMOS program. Expert Review of Endocrinology & Metabolism. 19(5). 419–428. 1 indexed citations
6.
Skudder‐Hill, Loren, Ivana R. Sequeira, Juyeon Ko, Sally D. Poppitt, & Maxim S. Petrov. (2024). The moderating effect of cardiometabolic factors on the association between hepatic and intrapancreatic fat. Obesity. 32(12). 2310–2320. 8 indexed citations
7.
Liu, Yutong, et al.. (2024). Intra‐pancreatic fat is associated with continuous glucose monitoring metrics. Diabetes Obesity and Metabolism. 26(6). 2359–2367. 6 indexed citations
8.
Goodarzi, Mark O. & Maxim S. Petrov. (2023). Diabetes of the Exocrine Pancreas: Implications for Pharmacological Management. Drugs. 83(12). 1077–1090. 15 indexed citations
9.
Ko, Juyeon, et al.. (2023). Relationship of Serum Bile Acids with Fat Deposition in the Pancreas, Liver, and Skeletal Muscle. Clinical and Experimental Gastroenterology. Volume 16. 137–146. 5 indexed citations
10.
Kimita, Wandia, Juyeon Ko, & Maxim S. Petrov. (2023). Relationship of Iron Intake, Ferritin, and Hepcidin with the Transverse Relaxation Rate of Water Protons in the Pancreas. Nutrients. 15(17). 3727–3727. 3 indexed citations
11.
12.
Singh, Ruma G., et al.. (2021). Association between Intrapancreatic Fat Deposition and the Leptin/Ghrelin Ratio in the Fasted and Postprandial States. Annals of Nutrition and Metabolism. 78(1). 14–20. 6 indexed citations
14.
Kumar, Haribalan, Steve V. DeSouza, & Maxim S. Petrov. (2019). Automated pancreas segmentation from computed tomography and magnetic resonance images: A systematic review. Computer Methods and Programs in Biomedicine. 178. 319–328. 53 indexed citations
15.
Merry, Troy L. & Maxim S. Petrov. (2018). The rise of genetically engineered mouse models of pancreatitis: A review of literature. BioMolecular Concepts. 9(1). 103–114. 11 indexed citations
16.
Petrov, Maxim S., et al.. (2018). Post-pancreatitis diabetes mellitus: towards understanding the role of gastrointestinal motility. PubMed. 64(4). 363–375. 6 indexed citations
17.
Pendharkar, Sayali A., et al.. (2017). Ethnic and geographic variations in the incidence of pancreatitis and post-pancreatitis diabetes mellitus in New Zealand: a nationwide population-based study.. PubMed. 130(1450). 55–68. 37 indexed citations
18.
Petrov, Maxim S., et al.. (2016). Protease-Related Predictors of Acute Pancreatitis Severity: A Systematic Review of the Literature. JOP, journal of the pancreas. 17(6). 2 indexed citations
19.
Singh, Primal P., et al.. (2013). Newly diagnosed diabetes mellitus after acute pancreatitis: a systematic review and meta-analysis. Gut. 63(5). 818–831. 259 indexed citations
20.
Petrov, Maxim S., Hjalmar C. van Santvoort, Marc G. Besselink, et al.. (2008). Early endoscopic retrograde cholangiopancreatography versus conservative management in acute biliary pancreatitis without cholangitis: a meta-analysis of randomized trials, in: Ann Surg, 247 (2008), 250. 145(3). 294. 1 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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