Anna Maria Paganoni

2.4k total citations
108 papers, 1.4k citations indexed

About

Anna Maria Paganoni is a scholar working on Statistics and Probability, Artificial Intelligence and Cardiology and Cardiovascular Medicine. According to data from OpenAlex, Anna Maria Paganoni has authored 108 papers receiving a total of 1.4k indexed citations (citations by other indexed papers that have themselves been cited), including 39 papers in Statistics and Probability, 20 papers in Artificial Intelligence and 14 papers in Cardiology and Cardiovascular Medicine. Recurrent topics in Anna Maria Paganoni's work include Statistical Methods and Inference (25 papers), Advanced Statistical Methods and Models (14 papers) and Bayesian Methods and Mixture Models (11 papers). Anna Maria Paganoni is often cited by papers focused on Statistical Methods and Inference (25 papers), Advanced Statistical Methods and Models (14 papers) and Bayesian Methods and Mixture Models (11 papers). Anna Maria Paganoni collaborates with scholars based in Italy, United Kingdom and France. Anna Maria Paganoni's co-authors include Francesca Ieva, Piercesare Secchi, Chiara Masci, Alberto Barchielli, Tommaso Agasisti, Laura M. Sangalli, Valeria Vitelli, Davide Pigoli, Simonetta Scalvini and Maria Pia Protti and has published in prestigious journals such as Journal of Clinical Oncology, The Journal of Immunology and PLoS ONE.

In The Last Decade

Anna Maria Paganoni

103 papers receiving 1.4k citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Anna Maria Paganoni Italy	22	259	228	203	179	179	108	1.4k
Sanjib Basu United States	29	339 1.3×	134 0.6×	175 0.9×	301 1.7×	287 1.6×	164	2.5k
Chris J. Lloyd Australia	23	621 2.4×	173 0.8×	132 0.7×	78 0.4×	129 0.7×	134	1.8k
J. Sunil Rao United States	20	474 1.8×	335 1.5×	33 0.2×	138 0.8×	222 1.2×	77	1.9k
Kenneth Jung United States	19	67 0.3×	409 1.8×	384 1.9×	97 0.5×	181 1.0×	27	2.5k
Paul Kirk United Kingdom	24	101 0.4×	180 0.8×	100 0.5×	273 1.5×	82 0.5×	64	2.4k
Martin Bøgsted Denmark	25	89 0.3×	73 0.3×	328 1.6×	57 0.3×	158 0.9×	161	2.3k
Vanessa Didelez Germany	23	817 3.2×	214 0.9×	44 0.2×	95 0.5×	118 0.7×	77	2.3k
Yuan Wu United States	22	140 0.5×	219 1.0×	91 0.4×	19 0.1×	138 0.8×	112	1.7k
Christopher R. Palmer United Kingdom	20	48 0.2×	218 1.0×	92 0.5×	143 0.8×	334 1.9×	28	1.6k
Lei Nie United States	22	659 2.5×	68 0.3×	304 1.5×	46 0.3×	55 0.3×	72	2.0k

Countries citing papers authored by Anna Maria Paganoni

Since Specialization

Citations

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

Fields of papers citing papers by Anna Maria Paganoni

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Anna Maria Paganoni. 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 Anna Maria Paganoni. The network helps show where Anna Maria Paganoni may publish in the future.

Co-authorship network of co-authors of Anna Maria Paganoni

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

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

Colecchia, Maurizio, et al.. (2022). Total embedding of spermatic cord and hilar soft tissue in orchiectomy for seminoma: does the extensive sampling improve pathologic risk factors?. Archiv für Pathologische Anatomie und Physiologie und für Klinische Medicin. 481(5). 695–701.

Masci, Chiara, et al.. (2021). Generalized mixed‐effects random forest: A flexible approach to predict university student dropout. Statistical Analysis and Data Mining The ASA Data Science Journal. 14(3). 241–257. 37 indexed citations

Scalvini, Simonetta, Francesco Grossetti, Anna Maria Paganoni, et al.. (2019). Impact of in-hospital cardiac rehabilitation on mortality and readmissions in heart failure: A population study in Lombardy, Italy, from 2005 to 2012. European Journal of Preventive Cardiology. 26(8). 808–817. 37 indexed citations

Fontana, Luca & Anna Maria Paganoni. (2018). Analysis of dropout in engineering BSc using logistic mixed-effect models.. Virtual Community of Pathological Anatomy (University of Castilla La Mancha). 1–6. 2 indexed citations

Ieva, Francesca, et al.. (2017). Nonparametric shared frailty model for classification of survival data. 1 indexed citations

Taroni, Paola, Anna Maria Paganoni, Francesca Ieva, et al.. (2017). Non-invasive optical estimate of tissue composition to differentiate malignant from benign breast lesions: A pilot study. Scientific Reports. 7(1). 40683–40683. 56 indexed citations

Frigerio, Maria, Cristina Mazzali, Anna Maria Paganoni, et al.. (2017). Trends in heart failure hospitalizations, patient characteristics, in-hospital and 1-year mortality: A population study, from 2000 to 2012 in Lombardy. International Journal of Cardiology. 236. 310–314. 14 indexed citations

Monte, Lucia De, Sonja M. Wörmann, Emanuela Brunetto, et al.. (2016). Basophil Recruitment into Tumor-Draining Lymph Nodes Correlates with Th2 Inflammation and Reduced Survival in Pancreatic Cancer Patients. Cancer Research. 76(7). 1792–1803. 124 indexed citations

Ieva, Francesca, et al.. (2016). Covariance-based clustering in multivariate and functional data analysis. Journal of Machine Learning Research. 17(1). 4985–5005. 5 indexed citations

10.

Ieva, Francesca, et al.. (2016). Dynamic clustering of hazard functions: an application to disease progression in chronic heart failure. Health Care Management Science. 20(3). 353–364. 5 indexed citations

11.

Guglielmi, Alessandra, et al.. (2016). A semiparametric Bayesian joint model for multiple mixed-type outcomes: an application to acute myocardial infarction. Advances in Data Analysis and Classification. 12(2). 399–423. 2 indexed citations

12.

Villafañe, Jorge Hugo, Lucia Bertozzi, Angiola Rocino, et al.. (2016). Validation of the Italian Version of the Haemophilia Activities List. Acta Haematologica. 136(3). 152–156. 2 indexed citations

13.

Ieva, Francesca, et al.. (2015). Use of Depth Measure for Multivariate Functional Data in Disease Prediction: An Application to Electrocardiograph Signals. The International Journal of Biostatistics. 11(2). 189–201. 5 indexed citations

14.

Ieva, Francesca, et al.. (2013). Operational Risk Management: a statistical perspective. Archivio Istituzionale della Ricerca (Universita Degli Studi Di Milano). 2013(2). 123–138. 2 indexed citations

15.

Guglielmi, Alessandra, et al.. (2013). Semiparametric Bayesian Models for Clustering and Classification in the Presence of Unbalanced In-Hospital Survival. Journal of the Royal Statistical Society Series C (Applied Statistics). 63(1). 25–46. 14 indexed citations

16.

Lullo, Giulia Di, Francesca Ieva, Renato Longhi, Anna Maria Paganoni, & Maria Pia Protti. (2012). Estimating Point and Interval Frequency of Antigen-Specific CD4+ T Cells Based on Short In Vitro Expansion and Improved Poisson Distribution Analysis. PLoS ONE. 7(8). e42340–e42340. 3 indexed citations

17.

Ieva, Francesca & Anna Maria Paganoni. (2010). Multilevel models for clinical registers concerning STEMI patients in a complex urban reality: a statistical analysis of MOMI2 survey. Archivio Istituzionale della Ricerca (Universita Degli Studi Di Milano). 1(1). 128–147. 7 indexed citations

18.

Origoni, Massimo, Flavia Lillo, Anna Maria Paganoni, et al.. (2007). IFN-γ Produced by Human Papilloma Virus-18 E6-Specific CD4+ T Cells Predicts the Clinical Outcome after Surgery in Patients with High-Grade Cervical Lesions. The Journal of Immunology. 179(10). 7176–7183. 41 indexed citations

19.

Paganoni, Anna Maria & Piercesare Secchi. (2007). A numerical study for comparing two response-adaptive designs for continuous treatment effects. Statistical Methods & Applications. 16(3). 321–346. 13 indexed citations

20.

May, Caterina, Anna Maria Paganoni, & Piercesare Secchi. (2005). On a two-color generalized Polya urn. METRON. 63(1). 115–134. 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.

Explore authors with similar magnitude of impact