Claudia Mazo
- Artificial Intelligence top 5%
- Health Informatics top 0.5%
- Radiology, Nuclear Medicine and Imaging top 10%
- Health Information Management top 5%
- Molecular Biology
- Co-authors
- Catherine MooneyYuhan DuBrett A. BeckerAnna Markella AntoniadiLan WeiMaría TrujilloJosé BernalEnrique Alegre
- Topics
- AI in cancer detection (8 papers)Radiomics and Machine Learning in Medical Imaging (6 papers)Biomedical Text Mining and Ontologies (4 papers)
In The Last Decade
Claudia Mazo
17 papers receiving 608 citations
Hit Papers
Peers
Comparison fields: 5 of 128
- Artificial Intelligence 332
- Health Informatics 170
- Radiology, Nuclear Medicine and Imaging 159
- Health Information Management 63
- Molecular Biology 57
Countries citing papers authored by Claudia Mazo
This map shows the geographic impact of Claudia Mazo'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 Claudia Mazo with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Claudia Mazo more than expected).
Fields of papers citing papers by Claudia Mazo
This network shows the impact of papers produced by Claudia Mazo. 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 Claudia Mazo. The network helps show where Claudia Mazo may publish in the future.
Co-authorship network of co-authors of Claudia Mazo
This figure shows the co-authorship network connecting the top 25 collaborators of Claudia Mazo. A scholar is included among the top collaborators of Claudia Mazo 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 Claudia Mazo. Claudia Mazo 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 | 2 | |
| 3 | 2 | |
| 4 | 0 | |
| 5 | 19 | |
| 6 | 28 | |
| 7 | 8 | |
| 8 | 27 | |
| 9 | Current Challenges and Future Opportunities for XAI in Machine Learning-Based Clinical Decision Support Systems: A Systematic Reviewbreakdown → | 347 |
| 10 | 60 | |
| 11 | 3 | |
| 12 | 16 | |
| 13 | 3 | |
| 14 | 5 | |
| 15 | 59 | |
| 16 | Desarrollo del banco de imágenes histológicas sobre el sistema cardiovascular (BISCAR) [recurso electrónico] | 0 |
| 17 | 9 | |
| 18 | 26 | |
| 19 | 7 | |
| 20 | 3 |
About Claudia Mazo
Claudia Mazo is a scholar working on Health Informatics, Health Information Management and Artificial Intelligence, having authored 21 papers that have together received 624 indexed citations. Recurring topics across this work include AI in cancer detection (8 papers), Radiomics and Machine Learning in Medical Imaging (6 papers) and Biomedical Text Mining and Ontologies (4 papers). The work is most often cited by research in Health Informatics (170 citations), Health Information Management (63 citations) and Artificial Intelligence (332 citations). Claudia Mazo has collaborated with scholars based in Ireland, Colombia and Spain. Frequent co-authors include Catherine Mooney, Yuhan Du, Brett A. Becker, Anna Markella Antoniadi, Lan Wei, María Trujillo, José Bernal, Enrique Alegre, William M. Gallagher and Arman Rahman. Their work appears in journals such as Scientific Reports, Annals of Oncology and Journal of Clinical Pathology.
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.