Noemi Gozzi
Impact in
- Health Informatics top 10%
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- Radiomics and Machine Learning in Medical Imaging
- Medical Imaging Techniques and Applications
- Radiopharmaceutical Chemistry and Applications
Papers in
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- Radiomics and Machine Learning in Medical Imaging 5
-
- Transcranial Magnetic Stimulation Studies 2
- Co-authors
- Arturo Chiti (9 shared papers)Martina Sollini (8 shared papers)Margarita Kirienko (6 shared papers)Fabrizia Gelardi (3 shared papers)Francesco Fiz (1 shared paper)Alessandra Pedrocchi (1 shared paper)Fabio Mercorio (1 shared paper)Lorenzo Malandri (1 shared paper)
- Journals
- European Journal of Nuclear Medicine and Molecular Imaging (5 papers)Nature Communications (2 papers)Artificial Intelligence in Medicine (1 paper)Knowledge-Based Systems (1 paper)Neuro-Oncology (1 paper)
- Partner nations
- ItalySwitzerlandAustria
In The Last Decade
Noemi Gozzi
17 papers receiving 409 citations
Peers
Comparison fields: 5 of 77
- Health Informatics 18
- Radiology, Nuclear Medicine and Imaging 124
- Oncology 114
- Cancer Research 59
- Genetics 25
Countries citing papers authored by Noemi Gozzi
This map shows the geographic impact of Noemi Gozzi'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 Noemi Gozzi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Noemi Gozzi more than expected).
Fields of papers citing papers by Noemi Gozzi
This network shows the impact of papers produced by Noemi Gozzi. 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 Noemi Gozzi. The network helps show where Noemi Gozzi may publish in the future.
Co-authors
The 25 scholars most cited alongside Noemi Gozzi, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2021 | 132 | |
| 2 | 2021 | 85 | |
| 3 | 2022 | 46 | |
| 4 | 2021 | 34 | |
| 5 | 2022 | 31 | |
| 6 | 2023 | 15 | |
| 7 | 2024 | 13 | |
| 8 | 2024 | 13 | |
| 9 | 2024 | 13 | |
| 10 | 2022 | 8 | |
| 11 | 2023 | 7 | |
| 12 | 2023 | 4 | |
| 13 | 2021 | 4 | |
| 14 | 2021 | 4 | |
| 15 | 2023 | 2 | |
| 16 | 2021 | 1 | |
| 17 | 2021 | 1 | |
| 18 | 2025 | 0 | |
| 19 | 2025 | 0 |
About Noemi Gozzi
Noemi Gozzi is a scholar working on Radiology, Nuclear Medicine and Imaging, Neurology, Cognitive Neuroscience, Biomedical Engineering and Cellular and Molecular Neuroscience, having authored 19 papers that have together received 413 indexed citations. Recurring topics across this work include Radiomics and Machine Learning in Medical Imaging (5 papers), Muscle activation and electromyography studies (3 papers), Neuroscience and Neural Engineering (2 papers), EEG and Brain-Computer Interfaces (2 papers), AI in cancer detection (2 papers), Transcranial Magnetic Stimulation Studies (2 papers), Cancer Genomics and Diagnostics (1 paper) and Gender Diversity and Inequality (1 paper). The work is most often cited by research in Health Informatics (18 citations), Radiology, Nuclear Medicine and Imaging (124 citations), Oncology (114 citations), Cancer Research (59 citations) and Genetics (25 citations). Noemi Gozzi has collaborated with scholars based in Italy, Switzerland and Austria. Frequent co-authors include Arturo Chiti, Martina Sollini, Margarita Kirienko, Fabrizia Gelardi, Francesco Fiz, Alessandra Pedrocchi, Fabio Mercorio, Lorenzo Malandri, Staniša Raspopović and Francesca Gallivanone. Their work appears in journals such as European Journal of Nuclear Medicine and Molecular Imaging, Nature Communications, Artificial Intelligence in Medicine, Knowledge-Based Systems and Neuro-Oncology.
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.