Daniela Said
Impact in
- Hepatology top 5%
- Hepatocellular Carcinoma Treatment and Prognosis
- Liver Disease and Transplantation
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- Radiomics and Machine Learning in Medical Imaging
- MRI in cancer diagnosis
Papers in
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- Radiomics and Machine Learning in Medical Imaging 6
- MRI in cancer diagnosis 6
- Advanced MRI Techniques and Applications 1
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- Hepatocellular Carcinoma Treatment and Prognosis 7
- Liver Disease and Transplantation 2
- Co-authors
- Bachir Taouli (10 shared papers)Sara Lewis (9 shared papers)Stefanie J. Hectors (8 shared papers)Octavia Bane (7 shared papers)Daniel Stocker (6 shared papers)Myron Schwartz (2 shared papers)Swan N. Thung (2 shared papers)Cecilia Besa (1 shared paper)
- Journals
- European Radiology (7 papers)Abdominal Radiology (2 papers)Radiology Imaging Cancer (1 paper)
- Partner nations
- United StatesChileSwitzerland
In The Last Decade
Daniela Said
10 papers receiving 299 citations
Peers
Comparison fields: 5 of 35
- Hepatology 178
- Radiology, Nuclear Medicine and Imaging 219
- Health Informatics 9
- Pulmonary and Respiratory Medicine 90
- Epidemiology 79
Countries citing papers authored by Daniela Said
This map shows the geographic impact of Daniela Said'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 Daniela Said with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Daniela Said more than expected).
Fields of papers citing papers by Daniela Said
This network shows the impact of papers produced by Daniela Said. 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 Daniela Said. The network helps show where Daniela Said may publish in the future.
Co-authors
The 25 scholars most cited alongside Daniela Said, 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 | 2020 | 110 | |
| 2 | 2020 | 56 | |
| 3 | 2020 | 42 | |
| 4 | 2021 | 29 | |
| 5 | 2022 | 18 | |
| 6 | 2020 | 16 | |
| 7 | 2023 | 12 | |
| 8 | 2021 | 6 | |
| 9 | 2020 | 6 | |
| 10 | 2021 | 5 |
About Daniela Said
Daniela Said is a scholar working on Radiology, Nuclear Medicine and Imaging, Hepatology, Pulmonary and Respiratory Medicine, Epidemiology and Biomedical Engineering, having authored 10 papers that have together received 300 indexed citations. Recurring topics across this work include Hepatocellular Carcinoma Treatment and Prognosis (7 papers), Radiomics and Machine Learning in Medical Imaging (6 papers), MRI in cancer diagnosis (6 papers), Liver Disease Diagnosis and Treatment (3 papers), Liver Disease and Transplantation (2 papers), Renal cell carcinoma treatment (2 papers), Advanced MRI Techniques and Applications (1 paper) and Advanced X-ray and CT Imaging (1 paper). The work is most often cited by research in Hepatology (178 citations), Radiology, Nuclear Medicine and Imaging (219 citations), Health Informatics (9 citations), Pulmonary and Respiratory Medicine (90 citations) and Epidemiology (79 citations). Daniela Said has collaborated with scholars based in United States, Chile and Switzerland. Frequent co-authors include Bachir Taouli, Sara Lewis, Stefanie J. Hectors, Octavia Bane, Daniel Stocker, Myron Schwartz, Swan N. Thung, Cecilia Besa, Yujin Hoshida and Stephen C. Ward. Their work appears in journals such as European Radiology, Abdominal Radiology and Radiology Imaging Cancer.
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.