M. Barbetti

2.9k citations
6 papers · 20 · h-index 2

Impact in

Papers in

M. Barbetti

5 papers receiving 20 citations

Peers

M. Barbetti
Comparison fields: 5 of 11
  • Radiology, Nuclear Medicine and Imaging 15
  • Pathology and Forensic Medicine 6
  • Nuclear and High Energy Physics 4
  • Pulmonary and Respiratory Medicine 4
  • Biomedical Engineering 5
Replace Chengrong Mi with:
Chengrong Mi China
A. Caringi United States
Xudong Lyu China
Supawan Surukrattanaskul Thailand
Angelakis Malamas Greece
Sutha Sanmugasundram Australia
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P. Modesto Switzerland
A. Moussa Morocco
H. Kim South Korea
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Citations per field
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Citations per year

Countries citing papers authored by M. Barbetti

Since Specialization
Citations

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

Fields of papers citing papers by M. Barbetti

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside M. Barbetti, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with M. Barbetti Line = papers co-authored together M. Barbetti links everyone, so they are left out of the graph.

All Works

6 of 6 papers shown
#Work
1 202315
2 20232
3 20221
4 20221
5 20221
6 20240

About M. Barbetti

M. Barbetti is a scholar working on Nuclear and High Energy Physics, Artificial Intelligence, Radiology, Nuclear Medicine and Imaging, Computer Networks and Communications and Pathology and Forensic Medicine, having authored 6 papers that have together received 20 indexed citations. Recurring topics across this work include Particle physics theoretical and experimental studies (4 papers), Particle Detector Development and Performance (3 papers), Computational Physics and Python Applications (2 papers), Generative Adversarial Networks and Image Synthesis (1 paper), Lymphoma Diagnosis and Treatment (1 paper), Parallel Computing and Optimization Techniques (1 paper), Medical Imaging Techniques and Applications (1 paper) and Radiomics and Machine Learning in Medical Imaging (1 paper). The work is most often cited by research in Radiology, Nuclear Medicine and Imaging (15 citations), Pathology and Forensic Medicine (6 citations), Nuclear and High Energy Physics (4 citations), Pulmonary and Respiratory Medicine (4 citations) and Biomedical Engineering (5 citations). M. Barbetti has collaborated with scholars based in Italy, Russia and Switzerland. Frequent co-authors include A. Maevskiy, Flavia Linguanti, Raffaella Santi, Valentina Berti, Alessandro Passeri, Francesco Mungai, Angelina Cistaro, Benedetta Sordi, L. Anderlini and Luca Nassi. Their work appears in journals such as Cancers, Nuclear Instruments and Methods in Physics Research Section A Accelerators Spectrometers Detectors and Associated Equipment, SHILAP Revista de lepidopterología, Journal of Physics Conference Series and Proceedings of 41st International Conference on High Energy physics — PoS(ICHEP2022).

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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