Matteo Mancini

96 total papers · 3.1k total citations
40 papers, 1.5k citations indexed

About

Matteo Mancini is a scholar working on Cognitive Neuroscience, Radiology, Nuclear Medicine and Imaging and Neurology. According to data from OpenAlex, Matteo Mancini has authored 40 papers receiving a total of 1.5k indexed citations (citations by other indexed papers that have themselves been cited), including 22 papers in Cognitive Neuroscience, 17 papers in Radiology, Nuclear Medicine and Imaging and 4 papers in Neurology. Recurrent topics in Matteo Mancini's work include Functional Brain Connectivity Studies (20 papers), Advanced Neuroimaging Techniques and Applications (12 papers) and Advanced MRI Techniques and Applications (9 papers). Matteo Mancini is often cited by papers focused on Functional Brain Connectivity Studies (20 papers), Advanced Neuroimaging Techniques and Applications (12 papers) and Advanced MRI Techniques and Applications (9 papers). Matteo Mancini collaborates with scholars based in Italy, United Kingdom and Canada. Matteo Mancini's co-authors include Mara Cercignani, Marco Bozzali, Maria Adele Signorini, Piero Bruschi, Ada Funaro, Federica Bevilacqua, Armando Gabrielli, Silvia Svegliati, Tatiana Spadoni and Enrico V. Avvedimento and has published in prestigious journals such as New England Journal of Medicine, PLoS ONE and NeuroImage.

In The Last Decade

Matteo Mancini

39 papers receiving 1.5k citations

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
Matteo Mancini 471 340 286 279 175 40 1.5k
Yi Chen 225 0.5× 235 0.7× 329 1.2× 137 0.5× 231 1.3× 73 1.4k
Hiroki Sasaki 467 1.0× 108 0.3× 100 0.3× 434 1.6× 515 2.9× 58 1.9k
M M Esiri 305 0.6× 216 0.6× 359 1.3× 98 0.4× 573 3.3× 42 1.9k
W. W. Tourtellotte 124 0.3× 401 1.2× 164 0.6× 137 0.5× 458 2.6× 47 1.9k
Julia Krämer 288 0.6× 443 1.3× 234 0.8× 517 1.9× 355 2.0× 54 1.8k
Mario Stampanoni Bassi 256 0.5× 503 1.5× 615 2.2× 57 0.2× 314 1.8× 71 1.8k
E. Bollen 392 0.8× 153 0.5× 222 0.8× 307 1.1× 198 1.1× 28 1.5k
Alexander Heß 289 0.6× 88 0.3× 464 1.6× 147 0.5× 389 2.2× 68 2.3k
Jochen G. Hirsch 270 0.6× 221 0.7× 108 0.4× 588 2.1× 177 1.0× 29 1.9k
Mariaemma Rodegher 332 0.7× 1.1k 3.4× 221 0.8× 385 1.4× 223 1.3× 47 1.6k

Countries citing papers authored by Matteo Mancini

Since Specialization
Citations

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

Fields of papers citing papers by Matteo Mancini

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Matteo Mancini

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

All Works

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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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