Diletta Cozzi
Impact in
- Health Informatics top 5%
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- Radiomics and Machine Learning in Medical Imaging
- COVID-19 diagnosis using AI
Papers in
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- Ultrasound in Clinical Applications 8
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- Radiomics and Machine Learning in Medical Imaging 16
- COVID-19 diagnosis using AI 8
- Co-authors
- Vittorio MieleEdoardo CavigliChiara MoroniSilvia PradellaGinevra DantiAlessandra BindiVincenza GranataS. Busoni
- Journals
- La radiologia medica (16 papers)Journal of Personalized Medicine (5 papers)International Journal of Environmental Research and Public Health (5 papers)Tomography (2 papers)Cancers (2 papers)
- Partner nations
- ItalyUnited KingdomTunisia
In The Last Decade
Diletta Cozzi
62 papers receiving 1.3k citations
Peers
Comparison fields: 5 of 103
- Health Informatics 40
- Radiology, Nuclear Medicine and Imaging 601
- Critical Care and Intensive Care Medicine 111
- Internal Medicine 46
- Pulmonary and Respiratory Medicine 359
Countries citing papers authored by Diletta Cozzi
This map shows the geographic impact of Diletta Cozzi'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 Diletta Cozzi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Diletta Cozzi more than expected).
Fields of papers citing papers by Diletta Cozzi
This network shows the impact of papers produced by Diletta Cozzi. 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 Diletta Cozzi. The network helps show where Diletta Cozzi may publish in the future.
Co-authors
The 25 scholars most cited alongside Diletta Cozzi, 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 | 2025 | 0 | |
| 2 | 2024 | 2 | |
| 3 | 2024 | 2 | |
| 4 | 2024 | 4 | |
| 5 | 2023 | 6 | |
| 6 | 2023 | 3 | |
| 7 | 2023 | 12 | |
| 8 | 2023 | 1 | |
| 9 | 2023 | 2 | |
| 10 | 2022 | 34 | |
| 11 | 2022 | 19 | |
| 12 | 2021 | 22 | |
| 13 | 2021 | 28 | |
| 14 | 2020 | 195 | |
| 15 | 2020 | 35 | |
| 16 | 2020 | 10 | |
| 17 | 2020 | 3 | |
| 18 | 2019 | 12 | |
| 19 | 2018 | 16 | |
| 20 | 2017 | 24 |
About Diletta Cozzi
Diletta Cozzi is a scholar working on Critical Care and Intensive Care Medicine, Radiology, Nuclear Medicine and Imaging, Pulmonary and Respiratory Medicine, Internal Medicine and Health Informatics, having authored 68 papers that have together received 1.3k indexed citations. Recurring topics across this work include Radiomics and Machine Learning in Medical Imaging (16 papers), COVID-19 diagnosis using AI (8 papers), Ultrasound in Clinical Applications (8 papers), Neuroendocrine Tumor Research Advances (7 papers), Lung Cancer Diagnosis and Treatment (6 papers), Pancreatic and Hepatic Oncology Research (6 papers), Advanced X-ray and CT Imaging (5 papers) and COVID-19 Clinical Research Studies (5 papers). The work is most often cited by research in Health Informatics (40 citations), Radiology, Nuclear Medicine and Imaging (601 citations), Critical Care and Intensive Care Medicine (111 citations), Internal Medicine (46 citations) and Pulmonary and Respiratory Medicine (359 citations). Diletta Cozzi has collaborated with scholars based in Italy, United Kingdom and Tunisia. Frequent co-authors include Vittorio Miele, Edoardo Cavigli, Chiara Moroni, Silvia Pradella, Ginevra Danti, Alessandra Bindi, Vincenza Granata, S. Busoni, L.N. Mazzoni and Silvia Luvarà. Their work appears in journals such as La radiologia medica, Journal of Personalized Medicine, International Journal of Environmental Research and Public Health, Tomography and Cancers.
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.