Nadia Mammone
- Cognitive Neuroscience top 1%
- Signal Processing top 1%
- Cardiology and Cardiovascular Medicine top 5%
- Artificial Intelligence top 5%
- Neurology top 5%
- Co-authors
- Francesco Carlo MorabitoCosimo IeracitanoAmir HussainFabio La ForestaAlessia BramantiHojjat AdeliSilvia MarinoSimona De Salvo
- Topics
- EEG and Brain-Computer Interfaces (58 papers)Neural dynamics and brain function (29 papers)Functional Brain Connectivity Studies (25 papers)
- Partner nations
- ItalyUnited KingdomUnited States
In The Last Decade
Nadia Mammone
79 papers receiving 2.5k citations
Peers
Comparison fields: 5 of 129
- Cognitive Neuroscience 1.8k
- Signal Processing 573
- Cardiology and Cardiovascular Medicine 443
- Artificial Intelligence 343
- Neurology 271
Countries citing papers authored by Nadia Mammone
This map shows the geographic impact of Nadia Mammone'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 Nadia Mammone with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Nadia Mammone more than expected).
Fields of papers citing papers by Nadia Mammone
This network shows the impact of papers produced by Nadia Mammone. 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 Nadia Mammone. The network helps show where Nadia Mammone may publish in the future.
Co-authorship network of co-authors of Nadia Mammone
This figure shows the co-authorship network connecting the top 25 collaborators of Nadia Mammone. A scholar is included among the top collaborators of Nadia Mammone 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 Nadia Mammone. Nadia Mammone is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 3 | |
| 3 | 5 | |
| 4 | 0 | |
| 5 | 0 | |
| 6 | 102 | |
| 7 | 4 | |
| 8 | 34 | |
| 9 | 43 | |
| 10 | 235 | |
| 11 | 9 | |
| 12 | 80 | |
| 13 | 80 | |
| 14 | 1 | |
| 15 | Usage of network analysis to investigate Periodic Sharp Wave Complexes in EEGs of patients with sporadic CJD. | 0 |
| 16 | 94 | |
| 17 | 50 | |
| 18 | 18 | |
| 19 | 0 | |
| 20 | A New Approach Based On Wavelet-ICA Algorithms For Fetal Electrocardiogram Extraction | 45 |
About Nadia Mammone
Nadia Mammone is a scholar working on Cognitive Neuroscience, Signal Processing and Human-Computer Interaction, having authored 86 papers that have together received 2.6k indexed citations. Recurring topics across this work include EEG and Brain-Computer Interfaces (58 papers), Neural dynamics and brain function (29 papers) and Functional Brain Connectivity Studies (25 papers). The work is most often cited by research in Cognitive Neuroscience (1.8k citations), Signal Processing (573 citations) and Neurology (271 citations). Nadia Mammone has collaborated with scholars based in Italy, United Kingdom and United States. Frequent co-authors include Francesco Carlo Morabito, Cosimo Ieracitano, Amir Hussain, Fabio La Foresta, Alessia Bramanti, Hojjat Adeli, Silvia Marino, Simona De Salvo, Lilla Bonanno and Mario Versaci. Their work appears in journals such as IEEE Access, Sensors and International Journal of Environmental Research and Public Health.
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.