Michele Scagliarini

480 total citations
32 papers, 351 citations indexed

About

Michele Scagliarini is a scholar working on Statistics, Probability and Uncertainty, Statistics and Probability and Surgery. According to data from OpenAlex, Michele Scagliarini has authored 32 papers receiving a total of 351 indexed citations (citations by other indexed papers that have themselves been cited), including 24 papers in Statistics, Probability and Uncertainty, 14 papers in Statistics and Probability and 5 papers in Surgery. Recurrent topics in Michele Scagliarini's work include Advanced Statistical Process Monitoring (24 papers), Advanced Statistical Methods and Models (13 papers) and Scientific Measurement and Uncertainty Evaluation (11 papers). Michele Scagliarini is often cited by papers focused on Advanced Statistical Process Monitoring (24 papers), Advanced Statistical Methods and Models (13 papers) and Scientific Measurement and Uncertainty Evaluation (11 papers). Michele Scagliarini collaborates with scholars based in Italy and Poland. Michele Scagliarini's co-authors include Silvano Bordignon, Lorenzo Fuccio, Leonardo Frazzoni, Edgar Santos–Fernández, Andrea Belluzzi, Franco Bazzoli, Giorgio Battaglia, Giampaolo Ugolini, Giorgia Valpiani and Daniela Cocchi and has published in prestigious journals such as SHILAP Revista de lepidopterología, The American Journal of Gastroenterology and Gastrointestinal Endoscopy.

In The Last Decade

Michele Scagliarini

27 papers receiving 338 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Michele Scagliarini Italy 11 176 105 80 60 57 32 351
Vladimir Bacârea Romania 9 12 0.1× 56 0.5× 8 0.1× 8 0.1× 38 0.7× 30 322
Ahmed H. Abdellah Egypt 14 306 1.7× 57 0.5× 429 5.4× 38 0.6× 1 0.0× 40 615
Ayca Ozol-Godfrey United States 9 18 0.1× 12 0.1× 10 0.1× 45 0.8× 2 0.0× 22 302
Jian Pan China 8 7 0.0× 55 0.5× 2 0.0× 11 0.2× 14 0.2× 22 288
W M Cooke United Kingdom 8 15 0.1× 157 1.5× 5 0.1× 6 0.1× 67 1.2× 10 414
Yiping Yang China 10 24 0.1× 79 0.8× 217 2.7× 9 0.1× 41 396
Amporn Atsawarungruangkit United States 11 5 0.0× 63 0.6× 5 0.1× 4 0.1× 26 0.5× 30 272
C. Y. Wang United States 12 16 0.1× 8 0.1× 510 6.4× 18 0.3× 15 681
Vikas Kapoor United States 11 4 0.0× 119 1.1× 5 0.1× 35 0.6× 55 417

Countries citing papers authored by Michele Scagliarini

Since Specialization
Citations

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

Fields of papers citing papers by Michele Scagliarini

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Michele Scagliarini

This figure shows the co-authorship network connecting the top 25 collaborators of Michele Scagliarini. A scholar is included among the top collaborators of Michele Scagliarini 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 Michele Scagliarini. Michele Scagliarini 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.
Scagliarini, Michele. (2021). A sequential test and a sequential sampling plan based on the process capability index Cpmk. Computational Statistics. 37(3). 1523–1550. 2 indexed citations
2.
Scagliarini, Michele, et al.. (2020). Process Control Charts in Falls Prevention: The Experience of the Local Healthcare Authority of Romagna, Italy. Health and Technology. 10(5). 1207–1220. 1 indexed citations
3.
Scagliarini, Michele, et al.. (2020). Comparison of control charts for Poisson count data in health‐care monitoring. Applied Stochastic Models in Business and Industry. 37(1). 139–154. 9 indexed citations
4.
Scagliarini, Michele. (2018). A sequential hypothesis testing procedure for the process capability index Cpk. Quality and Reliability Engineering International. 34(5). 791–806. 9 indexed citations
5.
Portinari, Mattia, Michele Scagliarini, Giorgia Valpiani, et al.. (2018). Do I Need to Operate on That in the Middle of the Night? Development of a Nomogram for the Diagnosis of Severe Acute Cholecystitis. Journal of Gastrointestinal Surgery. 22(6). 1016–1025. 14 indexed citations
6.
Scagliarini, Michele, et al.. (2016). Monitoring operating room turnaround time: a retrospective analysis. International Journal of Health Care Quality Assurance. 29(3). 351–9. 3 indexed citations
7.
Scagliarini, Michele. (2016). A sequential hypothesis testing procedure for the process capability index Cpk. AMS Acta (University of Bologna). 4 indexed citations
8.
Bortoli, Nicola de, Leonardo Frazzoni, Edoardo Savarino, et al.. (2016). Functional Heartburn Overlaps With Irritable Bowel Syndrome More Often than GERD. The American Journal of Gastroenterology. 111(12). 1711–1717. 54 indexed citations
9.
Scaioli, Eleonora, Michele Scagliarini, Elisa Liverani, et al.. (2015). Clinical application of faecal calprotectin in ulcerative colitis patients. European Journal of Gastroenterology & Hepatology. 27(12). 1418–1424. 20 indexed citations
10.
Scaioli, Eleonora, et al.. (2015). Can fecal calprotectin better stratify Crohn's disease activity index?. PubMed. 28(2). 247–252. 10 indexed citations
11.
Scagliarini, Michele. (2014). A Method for Improving Multivariate Measurement Systems Assessment. Quality and Reliability Engineering International. 31(6). 977–988. 6 indexed citations
12.
Cocchi, Daniela & Michele Scagliarini. (2013). Effects of the two-component measurement error model on X control charts. SHILAP Revista de lepidopterología. 4 indexed citations
13.
Santos–Fernández, Edgar & Michele Scagliarini. (2012). MPCI: An R Package for Computing Multivariate Process Capability Indices. SHILAP Revista de lepidopterología. 2 indexed citations
14.
Santos–Fernández, Edgar & Michele Scagliarini. (2012). MPCI: AnRPackage for Computing Multivariate Process Capability Indices. Journal of Statistical Software. 47(7). 11 indexed citations
15.
Sartini, Alessandro, Giulia Roda, Alessandra Munarini, et al.. (2011). Fecal Detection of Mycobacterium avium Paratuberculosis Using the IS900 DNA Sequence in Crohn’s Disease and Ulcerative Colitis Patients and Healthy Subjects. Digestive Diseases and Sciences. 56(10). 2957–2962. 30 indexed citations
16.
Scagliarini, Michele. (2011). Multivariate process capability using principal component analysis in the presence of measurement errors. AStA Advances in Statistical Analysis. 95(2). 113–128. 21 indexed citations
17.
Scagliarini, Michele. (2009). Inference on C pk for autocorrelated data in the presence of random measurement errors. Journal of Applied Statistics. 37(1). 147–158. 8 indexed citations
18.
Scagliarini, Michele, et al.. (2008). Computing Multivariate Process Capability Indices (Excel). Journal of Modern Applied Statistical Methods. 7(1). 346–357. 1 indexed citations
19.
Bordignon, Silvano & Michele Scagliarini. (2005). Estimation ofCpm when Measurement Error is Present. Quality and Reliability Engineering International. 22(7). 787–801. 20 indexed citations
20.
Bordignon, Silvano & Michele Scagliarini. (2000). Monitoring algorithms for detecting changes in the ozone concentrations. Environmetrics. 11(2). 125–137. 10 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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