Marco Intraligi

531 total citations
18 papers, 387 citations indexed

About

Marco Intraligi is a scholar working on Surgery, Pulmonary and Respiratory Medicine and Gastroenterology. According to data from OpenAlex, Marco Intraligi has authored 18 papers receiving a total of 387 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Surgery, 4 papers in Pulmonary and Respiratory Medicine and 4 papers in Gastroenterology. Recurrent topics in Marco Intraligi's work include Helicobacter pylori-related gastroenterology studies (5 papers), Alzheimer's disease research and treatments (3 papers) and Dementia and Cognitive Impairment Research (3 papers). Marco Intraligi is often cited by papers focused on Helicobacter pylori-related gastroenterology studies (5 papers), Alzheimer's disease research and treatments (3 papers) and Dementia and Cognitive Impairment Research (3 papers). Marco Intraligi collaborates with scholars based in Italy, United States and Switzerland. Marco Intraligi's co-authors include Massimo Buscema, Enzo Grossi, Livio Cipolletta, Riccardo Marmo, G. Rotondano, M. Koch, Angelo Andriulli, S Cheng, Maria Cristina Patrosso and Lucy Vannella and has published in prestigious journals such as Journal of the American Geriatrics Society, The American Journal of Gastroenterology and Medical Physics.

In The Last Decade

Marco Intraligi

18 papers receiving 354 citations

Peers

Marco Intraligi

SURGE

RNMI

GASTR

ONCOL

Jihye Lim South Korea

Yeong Chan Lee South Korea

Katrine Meyer Lauritsen Denmark

Akhil Das United States

Raja-Elie E. Abdulnour United States

Rolv‐Ole Lindsetmo Norway

Michael Blankenburg Germany

Hamzaini Abdul Hamid Malaysia

Daniele Bottigliengo Italy

Sola Han South Korea

Jihye Lim South Korea

Marco Intraligi

44 ×0.5

47 ×0.6

SURGE

49 ×0.7

RNMI

16 ×0.3

GASTR

18 ×0.4

ONCOL

Citations per year, relative to Marco Intraligi Marco Intraligi (= 1×) peers Jihye Lim

Countries citing papers authored by Marco Intraligi

Since Specialization

Citations

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

Fields of papers citing papers by Marco Intraligi

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Marco Intraligi

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

All Works

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18 of 18 papers shown

Rotondano, G., Livio Cipolletta, Enzo Grossi, et al.. (2011). Artificial neural networks accurately predict mortality in patients with nonvariceal upper GI bleeding. Gastrointestinal Endoscopy. 73(2). 218–226.e2. 54 indexed citations

Buri, L., Angelo Zullo, Cesare Hassan, et al.. (2011). Upper GI endoscopy in elderly patients: predictive factors of relevant endoscopic findings. Internal and Emergency Medicine. 8(2). 141–146. 12 indexed citations

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

Buri, L., Cesare Hassan, Gianluca Bersani, et al.. (2009). Appropriateness Guidelines and Predictive Rules to Select Patients for Upper Endoscopy: A Nationwide Multicenter Study. The American Journal of Gastroenterology. 105(6). 1327–1337. 24 indexed citations

Lahner, Edith, Marco Intraligi, Massimo Buscema, et al.. (2008). Artificial neural networks in the recognition of the presence of thyroid disease in patients with atrophic body gastritis. World Journal of Gastroenterology. 14(4). 563–563. 33 indexed citations

Grossi, Enzo, Riccardo Marmo, Marco Intraligi, & Massimo Buscema. (2008). Artificial Neural Networks for Early Prediction of Mortality in Patients with Non Variceal Upper GI Bleeding (UGIB). PubMed. 1. BII.S814–BII.S814. 8 indexed citations

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

Buscema, Massimo, et al.. (2005). An optimized experimental protocol based on neuro-evolutionary algorithms. Artificial Intelligence in Medicine. 34(3). 279–305. 39 indexed citations

Penco, Silvana, Enzo Grossi, S Cheng, et al.. (2005). Assessment of the Role of Genetic Polymorphism in Venous Thrombosis Through Artificial Neural Networks. Annals of Human Genetics. 69(6). 693–706. 36 indexed citations

10.

Luca, Mónica Di, Enzo Grossi, Barbara Borroni, et al.. (2005). Artificial neural networks allow the use of simultaneous measurements of Alzheimer Disease markers for early detection of the disease. Journal of Translational Medicine. 3(1). 30–30. 26 indexed citations

11.

Penco, Silvana, Enzo Grossi, SW Cheng, et al.. (2005). Assessment of Genetic Polymorphism Role in Venous Thrombosis Through Artificial Neural Networks. 1 indexed citations

12.

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

13.

Buscema, Massimo, et al.. (2004). Artificial Neural Networks and Artificial Organisms Can Predict Alzheimer Pathology in Individual Patients Only on The Basis of Cognitive and Functional Status. Neuroinformatics. 2(4). 399–416. 20 indexed citations

14.

Vomweg, T. W., Massimo Buscema, H.‐U. Kauczor, et al.. (2003). Improved artificial neural networks in prediction of malignancy of lesions in contrast‐enhanced MR‐mammography. Medical Physics. 30(9). 2350–2359. 46 indexed citations

15.

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

16.

Grassi, M, et al.. (2002). Artificial neural network assessment of substitutive pharmacological treatments in hospitalised intravenous drug users. Artificial Intelligence in Medicine. 24(1). 37–49. 6 indexed citations

17.

Buscema, Massimo, et al.. (1998). Application of Artificial Neural Networks to Eating Disorders. Substance Use & Misuse. 33(3). 765–791. 4 indexed citations

18.

Buscema, Massimo, et al.. (1998). Artificial Neural Networks for Drug Vulnerability Recognition and Dynamic Scenarios Simulation. Substance Use & Misuse. 33(3). 587–623. 11 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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