Benedetta Bracci
Impact in
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- COVID-19 diagnosis using AI
- Radiomics and Machine Learning in Medical Imaging
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- Ultrasound in Clinical Applications
Papers in
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- Radiomics and Machine Learning in Medical Imaging 6
- COVID-19 diagnosis using AI 5
- Medical Imaging Techniques and Applications 2
- Radiation Dose and Imaging 2
- MRI in cancer diagnosis 2
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- COVID-19 Clinical Research Studies 5
- Co-authors
- Michela Polici (14 shared papers)Andrea Laghi (14 shared papers)Marta Zerunian (14 shared papers)Damiano Caruso (14 shared papers)Tiziano Polidori (13 shared papers)Gisella Guido (13 shared papers)Francesco Pucciarelli (12 shared papers)Carlotta Rucci (9 shared papers)
- Journals
- La radiologia medica (4 papers)Cancers (2 papers)International Journal of Molecular Sciences (2 papers)Insights into Imaging (1 paper)BioMed Research International (1 paper)
- Partner nations
- ItalyUnited StatesSwitzerland
In The Last Decade
Benedetta Bracci
17 papers receiving 744 citations
Benedetta Bracci's Hit Papers
Peers
Comparison fields: 5 of 70
- Radiology, Nuclear Medicine and Imaging 496
- Critical Care and Intensive Care Medicine 103
- Health Informatics 22
- Infectious Diseases 297
- Neurology 94
Countries citing papers authored by Benedetta Bracci
This map shows the geographic impact of Benedetta Bracci'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 Benedetta Bracci with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Benedetta Bracci more than expected).
Fields of papers citing papers by Benedetta Bracci
This network shows the impact of papers produced by Benedetta Bracci. 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 Benedetta Bracci. The network helps show where Benedetta Bracci may publish in the future.
Co-authors
The 25 scholars most cited alongside Benedetta Bracci, 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 | Chest CT Features of COVID-19 in Rome, Italy Hit paper breakdown → | 2020 | 416 |
| 2 | 2016 | 64 | |
| 3 | 2020 | 38 | |
| 4 | 2021 | 38 | |
| 5 | 2020 | 33 | |
| 6 | 2023 | 28 | |
| 7 | 2021 | 27 | |
| 8 | 2021 | 25 | |
| 9 | 2016 | 21 | |
| 10 | 2021 | 20 | |
| 11 | 2021 | 13 | |
| 12 | 2022 | 11 | |
| 13 | 2022 | 8 | |
| 14 | 2021 | 8 | |
| 15 | 2022 | 7 | |
| 16 | 2022 | 4 | |
| 17 | 2017 | 1 | |
| 18 | 2024 | 0 |
About Benedetta Bracci
Benedetta Bracci is a scholar working on Radiology, Nuclear Medicine and Imaging, Infectious Diseases, Surgery, Biomedical Engineering and Oncology, having authored 18 papers that have together received 762 indexed citations. Recurring topics across this work include Radiomics and Machine Learning in Medical Imaging (6 papers), COVID-19 diagnosis using AI (5 papers), COVID-19 Clinical Research Studies (5 papers), Advanced X-ray and CT Imaging (4 papers), Medical Imaging Techniques and Applications (2 papers), Radiation Dose and Imaging (2 papers), MRI in cancer diagnosis (2 papers) and COVID-19 and healthcare impacts (2 papers). The work is most often cited by research in Radiology, Nuclear Medicine and Imaging (496 citations), Critical Care and Intensive Care Medicine (103 citations), Health Informatics (22 citations), Infectious Diseases (297 citations) and Neurology (94 citations). Benedetta Bracci has collaborated with scholars based in Italy, United States and Switzerland. Frequent co-authors include Michela Polici, Andrea Laghi, Marta Zerunian, Damiano Caruso, Tiziano Polidori, Gisella Guido, Francesco Pucciarelli, Carlotta Rucci, Chiara De Dominicis and Susanna Esposito. Their work appears in journals such as La radiologia medica, Cancers, International Journal of Molecular Sciences, Insights into Imaging and BioMed Research International.
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.