Daniela Schenone
Impact in
- Health Informatics top 10%
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- Radiomics and Machine Learning in Medical Imaging
- MRI in cancer diagnosis
- Medical Imaging Techniques and Applications
Papers in
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- Radiomics and Machine Learning in Medical Imaging 4
- MRI in cancer diagnosis 1
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- Multiple Myeloma Research and Treatments 4
- Co-authors
- Alberto Tagliafico (5 shared papers)Michele Piana (8 shared papers)Anna Maria Massone (3 shared papers)Nehmat Houssami (1 shared paper)Lucia Romani (2 shared papers)Costanza Conti (1 shared paper)Alida Dominietto (4 shared papers)Cristina Campi (6 shared papers)
In The Last Decade
Daniela Schenone
11 papers receiving 332 citations
Peers
Comparison fields: 5 of 74
- Health Informatics 12
- Radiology, Nuclear Medicine and Imaging 154
- Hematology 21
- Artificial Intelligence 71
- Computer Vision and Pattern Recognition 43
Countries citing papers authored by Daniela Schenone
This map shows the geographic impact of Daniela Schenone'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 Schenone with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Daniela Schenone more than expected).
Fields of papers citing papers by Daniela Schenone
This network shows the impact of papers produced by Daniela Schenone. 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 Schenone. The network helps show where Daniela Schenone may publish in the future.
Co-authors
The 25 scholars most cited alongside Daniela Schenone, 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 | 2019 | 211 | |
| 2 | 2018 | 57 | |
| 3 | 2017 | 23 | |
| 4 | 2021 | 13 | |
| 5 | 2021 | 10 | |
| 6 | 2022 | 8 | |
| 7 | 2020 | 7 | |
| 8 | 2018 | 3 | |
| 9 | 2020 | 3 | |
| 10 | 2021 | 1 | |
| 11 | [Treatment of Taenia saginata infections in adults with a single oral dose of praziquantel (author's transl)]. | 1980 | 1 |
| 12 | 2023 | 0 | |
| 13 | 2020 | 0 |
About Daniela Schenone
Daniela Schenone is a scholar working on Radiology, Nuclear Medicine and Imaging, Hematology, Computer Vision and Pattern Recognition, Genetics and Neurology, having authored 13 papers that have together received 337 indexed citations. Recurring topics across this work include Radiomics and Machine Learning in Medical Imaging (4 papers), Multiple Myeloma Research and Treatments (4 papers), Image and Signal Denoising Methods (2 papers), Sarcoma Diagnosis and Treatment (1 paper), Amyotrophic Lateral Sclerosis Research (1 paper), Hepatocellular Carcinoma Treatment and Prognosis (1 paper), MRI in cancer diagnosis (1 paper) and Medical Image Segmentation Techniques (1 paper). The work is most often cited by research in Health Informatics (12 citations), Radiology, Nuclear Medicine and Imaging (154 citations), Hematology (21 citations), Artificial Intelligence (71 citations) and Computer Vision and Pattern Recognition (43 citations). Daniela Schenone has collaborated with scholars based in Italy, Australia and France. Frequent co-authors include Alberto Tagliafico, Michele Piana, Anna Maria Massone, Nehmat Houssami, Lucia Romani, Costanza Conti, Alida Dominietto, Cristina Campi, Liliana Belgioia and Federica Rossi. Their work appears in journals such as Biomedicines, Pattern Recognition, The Breast, Applied Mathematics and Computation and Cancer Imaging.
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.