Daniel Pinto dos Santos
- Radiology, Nuclear Medicine and Imaging top 0.5%
- Health Informatics top 0.01%
- Biomedical Engineering top 5%
- Pulmonary and Respiratory Medicine top 5%
- Artificial Intelligence top 2%
- Co-authors
- Bettina BaeßlerDavid MaintzRoman KloecknerSebastian BrodehlSeung‐Hun ChonKilian WeissRobert KleinertWieland Staab
- Topics
- Radiomics and Machine Learning in Medical Imaging (50 papers)Artificial Intelligence in Healthcare and Education (40 papers)Advanced X-ray and CT Imaging (33 papers)
- Journals
- Journal of Clinical OncologySHILAP Revista de lepidopterologíaPLoS ONE
- Partner nations
- GermanyUnited StatesSwitzerland
In The Last Decade
Daniel Pinto dos Santos
145 papers receiving 3.4k citations
Hit Papers
Peers
Comparison fields: 5 of 139
- Radiology, Nuclear Medicine and Imaging 1.9k
- Health Informatics 1.2k
- Biomedical Engineering 748
- Pulmonary and Respiratory Medicine 530
- Artificial Intelligence 502
Countries citing papers authored by Daniel Pinto dos Santos
This map shows the geographic impact of Daniel Pinto dos Santos'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 Daniel Pinto dos Santos with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Daniel Pinto dos Santos more than expected).
Fields of papers citing papers by Daniel Pinto dos Santos
This network shows the impact of papers produced by Daniel Pinto dos Santos. 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 Daniel Pinto dos Santos. The network helps show where Daniel Pinto dos Santos may publish in the future.
Co-authorship network of co-authors of Daniel Pinto dos Santos
This figure shows the co-authorship network connecting the top 25 collaborators of Daniel Pinto dos Santos. A scholar is included among the top collaborators of Daniel Pinto dos Santos based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Daniel Pinto dos Santos. Daniel Pinto dos Santos is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 8 | |
| 3 | 1 | |
| 4 | 2 | |
| 5 | 9 | |
| 6 | 2 | |
| 7 | 11 | |
| 8 | 26 | |
| 9 | 7 | |
| 10 | 22 | |
| 11 | 8 | |
| 12 | 29 | |
| 13 | 34 | |
| 14 | CheckList for EvaluAtion of Radiomics research (CLEAR): a step-by-step reporting guideline for authors and reviewers endorsed by ESR and EuSoMIIbreakdown → | 235 |
| 15 | 34 | |
| 16 | 2 | |
| 17 | 0 | |
| 18 | 14 | |
| 19 | 24 | |
| 20 | 1 |
About Daniel Pinto dos Santos
Daniel Pinto dos Santos is a scholar working on Health Informatics, Radiology, Nuclear Medicine and Imaging and Hepatology, having authored 154 papers that have together received 3.5k indexed citations. Recurring topics across this work include Radiomics and Machine Learning in Medical Imaging (50 papers), Artificial Intelligence in Healthcare and Education (40 papers) and Advanced X-ray and CT Imaging (33 papers). The work is most often cited by research in Health Informatics (1.2k citations), Radiology, Nuclear Medicine and Imaging (1.9k citations) and Hepatology (364 citations). Daniel Pinto dos Santos has collaborated with scholars based in Germany, United States and Switzerland. Frequent co-authors include Bettina Baeßler, David Maintz, Roman Kloeckner, Sebastian Brodehl, Seung‐Hun Chon, Kilian Weiss, Robert Kleinert, Wieland Staab, Daniel Giese and Christoph Düber. Their work appears in journals such as Journal of Clinical Oncology, SHILAP Revista de lepidopterología and PLoS ONE.
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.