Massimo Buscema

6.7k total citations
195 papers, 4.7k citations indexed

About

Massimo Buscema is a scholar working on Artificial Intelligence, Surgery and Endocrinology, Diabetes and Metabolism. According to data from OpenAlex, Massimo Buscema has authored 195 papers receiving a total of 4.7k indexed citations (citations by other indexed papers that have themselves been cited), including 40 papers in Artificial Intelligence, 35 papers in Surgery and 26 papers in Endocrinology, Diabetes and Metabolism. Recurrent topics in Massimo Buscema's work include Neural Networks and Applications (20 papers), Pancreatic function and diabetes (19 papers) and Alzheimer's disease research and treatments (12 papers). Massimo Buscema is often cited by papers focused on Neural Networks and Applications (20 papers), Pancreatic function and diabetes (19 papers) and Alzheimer's disease research and treatments (12 papers). Massimo Buscema collaborates with scholars based in Italy, United States and United Kingdom. Massimo Buscema's co-authors include Enzo Grossi, Paola Rossetti, Riccardo Vigneri, Antonio Simone Laganà, Salvatore Giovanni Vitale, Pier Luigi Sacco, Marco Intraligi, Agnese Maria Chiara Rapisarda, Paolo Maria Rossini and A. Nigro and has published in prestigious journals such as The Lancet, SHILAP Revista de lepidopterología and PLoS ONE.

In The Last Decade

Massimo Buscema

186 papers receiving 4.5k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Massimo Buscema Italy 36 701 551 547 542 534 195 4.7k
Herbert F. Jelinek Australia 39 818 1.2× 610 1.1× 545 1.0× 439 0.8× 329 0.6× 360 7.7k
Enzo Grossi Italy 44 976 1.4× 952 1.7× 375 0.7× 323 0.6× 929 1.7× 294 6.6k
Werner Vach Germany 52 778 1.1× 281 0.5× 432 0.8× 299 0.6× 1.3k 2.3× 397 9.3k
Harald Binder Germany 51 1.8k 2.6× 646 1.2× 216 0.4× 524 1.0× 938 1.8× 293 10.1k
David Cohen United States 42 2.1k 3.0× 472 0.9× 285 0.5× 298 0.5× 380 0.7× 251 7.0k
Wendy Lou Canada 39 617 0.9× 317 0.6× 490 0.9× 232 0.4× 368 0.7× 204 5.8k
Stephen Senn United Kingdom 42 366 0.5× 371 0.7× 199 0.4× 287 0.5× 493 0.9× 178 9.4k
Vivian Lee Hong Kong 43 1.2k 1.7× 134 0.2× 311 0.6× 344 0.6× 1.1k 2.0× 309 6.6k
Lin Shi China 39 439 0.6× 711 1.3× 156 0.3× 407 0.8× 792 1.5× 361 6.3k
Dimitris Rizopoulos Netherlands 43 438 0.6× 196 0.4× 221 0.4× 585 1.1× 988 1.9× 225 7.4k

Countries citing papers authored by Massimo Buscema

Since Specialization
Citations

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

Fields of papers citing papers by Massimo Buscema

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Massimo Buscema

This figure shows the co-authorship network connecting the top 25 collaborators of Massimo Buscema. A scholar is included among the top collaborators of Massimo Buscema 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 Massimo Buscema. Massimo Buscema 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.
Buscema, Massimo, et al.. (2023). A Pattern Recognition Analysis of Vessel Trajectories. Algorithms. 16(9). 414–414. 2 indexed citations
2.
D’Amico, Natascha Claudia, Enzo Grossi, Giovanni Valbusa, et al.. (2020). A machine learning approach for differentiating malignant from benign enhancing foci on breast MRI. European Radiology Experimental. 4(1). 5–5. 16 indexed citations
3.
Buscema, Massimo, Guido Ferilli, Christer Gustafsson, & Pier Luigi Sacco. (2019). The Complex Dynamic Evolution of Cultural Vibrancy in the Region of Halland, Sweden. International Regional Science Review. 43(3). 159–202. 6 indexed citations
4.
Alicandro, Maria, et al.. (2019). Shoreline Extraction Based on an Active Connection Matrix (ACM) Image Enhancement Strategy. Journal of Marine Science and Engineering. 8(1). 9–9. 32 indexed citations
5.
Dominici, Donatella, et al.. (2019). High Resolution Satellite Images for Instantaneous Shoreline Extraction Using New Enhancement Algorithms. Geosciences. 9(3). 123–123. 23 indexed citations
6.
Buscema, Massimo, et al.. (2017). The ANNS approach to DEM reconstruction. Computational Intelligence. 34(1). 310–344. 6 indexed citations
7.
Podda, Gian Marco, Enzo Grossi, Tullio Palmerini, et al.. (2017). Prediction of high on-treatment platelet reactivity in clopidogrel-treated patients with acute coronary syndromes. International Journal of Cardiology. 240. 60–65. 11 indexed citations
8.
Rizzo, Gianluca, Antonio Simone Laganà, Agnese Maria Chiara Rapisarda, et al.. (2016). Vitamin B12 among Vegetarians: Status, Assessment and Supplementation. Nutrients. 8(12). 767–767. 256 indexed citations
9.
Coppedè, Fabio, Enzo Grossi, Massimo Buscema, & Lucia Migliore. (2013). Application of Artificial Neural Networks to Investigate One-Carbon Metabolism in Alzheimer’s Disease and Healthy Matched Individuals. PLoS ONE. 8(8). e74012–e74012. 29 indexed citations
10.
Buri, L., Gianluca Bersani, Cesare Hassan, et al.. (2010). How to predict a high rate of inappropriateness for upper endoscopy in an endoscopic centre?. Digestive and Liver Disease. 42(9). 624–628. 4 indexed citations
11.
Buscema, Massimo & Enzo Grossi. (2008). The semantic connectivity map: an adapting self-organising knowledge discovery method in data bases. Experience in gastro-oesophageal reflux disease. International Journal of Data Mining and Bioinformatics. 2(4). 362–362. 74 indexed citations
12.
Buscema, Massimo, et al.. (2005). Sistemi ACM e Imaging Diagnostico: Le immagini mediche come Matrici Attive di Connessioni. Digital Access to Libraries (Université catholique de Louvain (UCL), l'Université de Namur (UNamur) and the Université Saint-Louis (USL-B)). 3 indexed citations
13.
Grossi, Enzo, et al.. (2005). Possible contribution of artificial neural networks and linear discriminant analysis in recognition of patients with suspected atrophic body gastritis. 世界胃肠病学杂志：英文版（电子版）. 11(37). 5867–5873. 3 indexed citations
14.
Pace, Fábio, Massimo Buscema, Marco Intraligi, et al.. (2005). Artificial neural networks are able to recognize gastro-oesophageal reflux disease patients solely on the basis of clinical data. European Journal of Gastroenterology & Hepatology. 17(6). 605–610. 29 indexed citations
15.
Grossi, Enzo, et al.. (2005). Two different Alzheimer diseases in men and women: Clues from advanced neural networks and artificial intelligence. Gender Medicine. 2(2). 106–117. 14 indexed citations
16.
Baldassarre, Damiano, Enzo Grossi, Massimo Buscema, et al.. (2004). Recognition of patients with cardiovascular disease by artificial neural networks. Annals of Medicine. 36(8). 630–640. 15 indexed citations
17.
Mecocci, Patrizia, Enzo Grossi, Massimo Buscema, et al.. (2002). Use of Artificial Networks in Clinical Trials: A Pilot Study to Predict Responsiveness to Donepezil in Alzheimer's Disease. Journal of the American Geriatrics Society. 50(11). 1857–1860. 19 indexed citations
18.
Regalbuto, Concetto, et al.. (1998). [Iodine deficiency and iodine prophylaxis experience in Sicily].. PubMed. 34(3). 429–36. 8 indexed citations
19.
Buscema, Massimo, et al.. (1992). Nicotinamide partially reverses the interleukin-1β inhibition of glucose-induced insulin release in pancreatic islets. Metabolism. 41(3). 296–300. 14 indexed citations
20.
Buscema, Massimo, et al.. (1981). Capacités morphogènes des cellules d’éponges dissociées. Flanders Marine Institute (Flanders Marine Institute). 5 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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