Marco Scutari

4.4k total citations · 2 hit papers
51 papers, 2.3k citations indexed

About

Marco Scutari is a scholar working on Artificial Intelligence, Pharmacology and Molecular Biology. According to data from OpenAlex, Marco Scutari has authored 51 papers receiving a total of 2.3k indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Artificial Intelligence, 8 papers in Pharmacology and 6 papers in Molecular Biology. Recurrent topics in Marco Scutari's work include Bayesian Modeling and Causal Inference (13 papers), Musculoskeletal pain and rehabilitation (8 papers) and Mental Health Research Topics (6 papers). Marco Scutari is often cited by papers focused on Bayesian Modeling and Causal Inference (13 papers), Musculoskeletal pain and rehabilitation (8 papers) and Mental Health Research Topics (6 papers). Marco Scutari collaborates with scholars based in Switzerland, United Kingdom and United States. Marco Scutari's co-authors include Radhakrishnan Nagarajan, Jean‐Baptiste Denis, Sophie Lèbre, Giovanni Briganti, Richard J. McNally, Phil Howell, Ian Mackay, David J. Balding, Paul Linkowski and Bernard X. W. Liew and has published in prestigious journals such as PLoS ONE, Scientific Reports and Genetics.

In The Last Decade

Marco Scutari

47 papers receiving 2.3k citations

Hit 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.

Learning Bayesian Networks with thebnlearnRPackage

2010 1.1k citations Marco Scutari profile →
A tutorial on bayesian networks for psychopathology researchers.

2022 96 citations Marco Scutari et al. Psychological Methods profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Marco Scutari Switzerland	15	642	342	325	192	173	51	2.3k
Daniel J. Stekhoven Switzerland	13	644 1.0×	231 0.7×	605 1.9×	272 1.4×	82 0.5×	26	4.4k
Pascal Wild France	36	487 0.8×	224 0.7×	265 0.8×	90 0.5×	147 0.8×	233	5.3k
Yulia R. Gel United States	24	360 0.6×	131 0.4×	203 0.6×	105 0.5×	149 0.9×	110	3.2k
Gerhard Tutz Germany	9	372 0.6×	159 0.5×	162 0.5×	100 0.5×	159 0.9×	16	2.6k
Jacqueline J. Meulman Netherlands	30	592 0.9×	131 0.4×	308 0.9×	86 0.4×	154 0.9×	75	3.8k
Miron B. Kursa Poland	12	596 0.9×	99 0.3×	823 2.5×	190 1.0×	92 0.5×	24	4.6k
Alireza Daneshkhah United Kingdom	25	370 0.6×	168 0.5×	166 0.5×	60 0.3×	249 1.4×	96	3.5k
Thomas Augustin Germany	21	840 1.3×	114 0.3×	440 1.4×	266 1.4×	317 1.8×	127	4.4k
Gavin C. Cawley United Kingdom	23	1.1k 1.7×	106 0.3×	518 1.6×	77 0.4×	150 0.9×	82	4.3k
Luigi Salmaso Italy	26	310 0.5×	106 0.3×	174 0.5×	114 0.6×	424 2.5×	152	2.9k

Countries citing papers authored by Marco Scutari

Since Specialization

Citations

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

Fields of papers citing papers by Marco Scutari

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Marco Scutari

This figure shows the co-authorship network connecting the top 25 collaborators of Marco Scutari. A scholar is included among the top collaborators of Marco Scutari 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 Marco Scutari. Marco Scutari 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

Bernasconi, Alice, Peter Lucas, Johanna M.A. Pijnenborg, et al.. (2025). Federated causal discovery with missing data in a multicentric study on endometrial cancer. Journal of Biomedical Informatics. 169. 104877–104877.

Scutari, Marco, Jessica van Setten, Sander W. van der Laan, et al.. (2025). Technical and legal aspects of federated learning in bioinformatics: applications, challenges and opportunities. Frontiers in Digital Health. 7. 1644291–1644291.

Orsoni, Matteo, Mariagrazia Benassi, & Marco Scutari. (2025). Information theory, machine learning, and Bayesian networks in the analysis of dichotomous and Likert responses for questionnaire psychometric validation.. Psychological Methods.

Papanastasiou, Giorgos, et al.. (2025). Large scale causal modeling to identify adults at risk for combined and common variable immunodeficiencies. npj Digital Medicine. 8(1). 361–361. 1 indexed citations

Bernasconi, Alice, Peter Lucas, Marco Scutari, et al.. (2024). From Real-World Data to Causally Interpretable Models: A Bayesian Network to Predict Cardiovascular Diseases in Adolescents and Young Adults with Breast Cancer. Cancers. 16(21). 3643–3643. 1 indexed citations

Scutari, Marco. (2024). Entropy and the Kullback–Leibler Divergence for Bayesian Networks: Computational Complexity and Efficient Implementation. Algorithms. 17(1). 24–24. 2 indexed citations

Scutari, Marco, et al.. (2024). Inferring skin–brain–skin connections from infodemiology data using dynamic Bayesian networks. Scientific Reports. 14(1). 10266–10266. 3 indexed citations

Scutari, Marco, et al.. (2023). The Pragmatic Programmer for Machine Learning. 1 indexed citations

Scutari, Marco, Philippe Bijlenga, Sandrine Morel, et al.. (2022). Bayesian network analysis reveals the interplay of intracranial aneurysm rupture risk factors. Computers in Biology and Medicine. 147. 105740–105740. 12 indexed citations

10.

Liew, Bernard X. W., María Palacios‐Ceña, Marco Scutari, et al.. (2022). Path Analysis Models Integrating Psychological, Psycho-physical and Clinical Variables in Individuals With Tension-Type Headache. Journal of Pain. 24(3). 426–436. 5 indexed citations

11.

Scutari, Marco, et al.. (2021). A constraint-based algorithm for the structural learning of continuous-time Bayesian networks. BOA (University of Milano-Bicocca). 5 indexed citations

12.

Liew, Bernard X. W., Jon J. Ford, Marco Scutari, & Andrew J. Hahne. (2021). How does individualised physiotherapy work for people with low back pain? A Bayesian Network analysis using randomised controlled trial data. PLoS ONE. 16(10). e0258515–e0258515. 6 indexed citations

13.

Falla, Deborah, et al.. (2021). Self-efficacy beliefs mediate the association between pain intensity and pain interference in acute/subacute whiplash-associated disorders. European Spine Journal. 30(6). 1689–1698. 11 indexed citations

14.

Scutari, Marco, et al.. (2018). Who Learns Better Bayesian Network Structures: Constraint-Based, Score-based or Hybrid Algorithms?. arXiv (Cornell University). 416–427. 16 indexed citations

15.

Chao, Yi‐Sheng, Marco Scutari, Chao-Jung Wu, et al.. (2018). A network perspective of engaging patients in specialist and chronic illness care: The 2014 International Health Policy Survey. PLoS ONE. 13(8). e0201355–e0201355. 5 indexed citations

16.

Vitolo, Claudia, et al.. (2017). A multi-dimensional environment-health risk analysis system for the English regions. EGUGA. 11880. 1 indexed citations

17.

Scutari, Marco, Pietro Auconi, Guido Caldarelli, & Lorenzo Franchi. (2017). Bayesian Networks Analysis of Malocclusion Data. Scientific Reports. 7(1). 15236–15236. 28 indexed citations

18.

Chao, Yi‐Sheng, Hau‐Tieng Wu, Marco Scutari, et al.. (2017). A network perspective on patient experiences and health status: the Medical Expenditure Panel Survey 2004 to 2011. BMC Health Services Research. 17(1). 579–579. 13 indexed citations

19.

Puga, Jorge López, et al.. (2014). LEARNING A BAYESIAN STRUCTURE TO MODEL ATTITUDES TOWARDS BUSINESS CREATION AT UNIVERSITY. INTED2014 Proceedings. 5242–5249. 2 indexed citations

20.

Bentley, Alison R., Marco Scutari, N. Gosman, et al.. (2014). Applying association mapping and genomic selection to the dissection of key traits in elite European wheat. Theoretical and Applied Genetics. 127(12). 2619–2633. 76 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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