Daniel Pinto dos Santos

6.2k citations
154 papers · 3.5k indexed · 2 hit papers · h-index 28

Daniel Pinto dos Santos

145 papers receiving 3.4k citations

Hit Papers

Guiding AI in radiology: ES...24202320262024202550100150200

Peers

Daniel Pinto dos Santos
Comparison fields: 5 of 139
  • Health Informatics 1.2k
  • Radiology, Nuclear Medicine and Imaging 1.9k
  • Hepatology 364
  • Family Practice 98
  • General Dentistry 44
Replace Bettina Baeßler with:
Bettina Baeßler Germany
Garry Choy United States
Filippo Pesapane Italy
James H. Thrall United States
Emanuele Neri Italy
Marc Kohli United States
Adrian P. Brady Ireland
Keno K. Bressem Germany
William Parker Canada
Keith J. Dreyer United States
Daniel Pinto dos Santos relative to Bettina Baeßler Germany Bettina Baeßler's profile →
Citations per field
00.5×3.9×
Bettina Baeßler · 1×
Citations per year

Countries citing papers authored by Daniel Pinto dos Santos

Since Specialization
Citations

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

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

The 25 scholars most cited alongside Daniel Pinto dos Santos, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Daniel Pinto dos Santos Line = papers co-authored together Daniel Pinto dos Santos links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
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11 20238
12 202329
13 202334
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CheckList for EvaluAtion of Radiomics research (CLEAR): a step-by-step reporting guideline for authors and reviewers endorsed by ESR and EuSoMIIbreakdown →
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15 202334
16 20232
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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), Advanced X-ray and CT Imaging (33 papers), Radiology practices and education (31 papers), Radiation Dose and Imaging (26 papers), Hepatocellular Carcinoma Treatment and Prognosis (23 papers), Medical Imaging Techniques and Applications (13 papers) and Cholangiocarcinoma and Gallbladder Cancer Studies (11 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 European Radiology, Insights into Imaging, RöFo - Fortschritte auf dem Gebiet der Röntgenstrahlen und der bildgebenden Verfahren, European Journal of Radiology and Scientific Reports.

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.

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