Claudia Mazo

1.0k total citations · 1 hit paper
21 papers, 624 citations indexed

About

Claudia Mazo is a scholar working on Artificial Intelligence, Radiology, Nuclear Medicine and Imaging and Molecular Biology. According to data from OpenAlex, Claudia Mazo has authored 21 papers receiving a total of 624 indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Artificial Intelligence, 7 papers in Radiology, Nuclear Medicine and Imaging and 5 papers in Molecular Biology. Recurrent topics in Claudia Mazo's 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). Claudia Mazo is often cited by papers focused on AI in cancer detection (8 papers), Radiomics and Machine Learning in Medical Imaging (6 papers) and Biomedical Text Mining and Ontologies (4 papers). Claudia Mazo collaborates with scholars based in Ireland, Colombia and Spain. Claudia Mazo's 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 and has published in prestigious journals such as Scientific Reports, Annals of Oncology and Journal of Clinical Pathology.

In The Last Decade

Claudia Mazo

17 papers receiving 608 citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Current Challenges and Future Opportunities for XAI in Machine Learning-Based Clinical Decision Support Systems: A Systematic Review

2021 347 citations Anna Markella Antoniadi, Yuhan Du et al. Applied Sciences profile →

Peers

Claudia Mazo

AI

HI

RNMI

HIM

MB

Markus Plass Austria

Zahra Shakeri Hossein Abad Canada

Micah Sheller United States

Brandon Edwards United States

Sarthak Pati United States

Jason Martin United States

Daniel Rückert Germany

Helen Frazer Australia

Friederike Jungmann Germany

Yashbir Singh United States

Markus Plass Austria

Claudia Mazo

407 ×1.2

AI

148 ×0.9

HI

187 ×1.2

RNMI

25 ×0.4

HIM

61 ×1.1

MB

Citations per year, relative to Claudia Mazo Claudia Mazo (= 1×) peers Markus Plass

Countries citing papers authored by Claudia Mazo

Since Specialization

Citations

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

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

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20 of 20 papers shown

1.

Lohner, Valerie, AmanPreet Badhwar, Helena M. Gellersen, et al.. (2025). Machine learning applications in vascular neuroimaging for the diagnosis and prognosis of cognitive impairment and dementia: a systematic review and meta-analysis. Alzheimer s Research & Therapy. 17(1). 183–183.

2.

Mazo, Claudia, et al.. (2024). Transfer Learning Approach for Detecting Breast Cancer Tumour Subtypes in Whole-Slide Images. 1–4. 2 indexed citations

3.

Emmanuel, Sabu, et al.. (2024). Deep CNNs for Diabetic Retinopathy Classification: A Transfer Learning Perspective. 1–4. 2 indexed citations

4.

Mazo, Claudia, et al.. (2023). MRI and CT Fusion in Stereotactic Electroencephalography (SEEG). Diagnostics. 13(22). 3420–3420.

5.

Mazo, Claudia, Claudia Aura, Arman Rahman, William M. Gallagher, & Catherine Mooney. (2022). Application of Artificial Intelligence Techniques to Predict Risk of Recurrence of Breast Cancer: A Systematic Review. Journal of Personalized Medicine. 12(9). 1496–1496. 19 indexed citations

6.

Bernal, José & Claudia Mazo. (2022). Transparency of Artificial Intelligence in Healthcare: Insights from Professionals in Computing and Healthcare Worldwide. Applied Sciences. 12(20). 10228–10228. 28 indexed citations

7.

Mazo, Claudia, et al.. (2021). MRI and CT Fusion in Stereotactic Electroencephalography: A Literature Review. Applied Sciences. 11(12). 5524–5524. 8 indexed citations

8.

Higgins, Debra F., Claudia Mazo, William Watson, et al.. (2021). Future of biomarker evaluation in the realm of artificial intelligence algorithms: application in improved therapeutic stratification of patients with breast and prostate cancer. Journal of Clinical Pathology. 74(7). 429–434. 27 indexed citations

9.

Antoniadi, Anna Markella, Yuhan Du, Lan Wei, et al.. (2021). Current Challenges and Future Opportunities for XAI in Machine Learning-Based Clinical Decision Support Systems: A Systematic Review. Applied Sciences. 11(11). 5088–5088. 347 indexed citations breakdown →

10.

Mazo, Claudia, et al.. (2020). Clinical Decision Support Systems in Breast Cancer: A Systematic Review. Cancers. 12(2). 369–369. 60 indexed citations

11.

Mazo, Claudia, Enrique Alegre, & María Trujillo. (2020). Using an ontology of the human cardiovascular system to improve the classification of histological images. Scientific Reports. 10(1). 12276–12276. 3 indexed citations

12.

Mazo, Claudia, Stephen Barron, Catherine Mooney, & William M. Gallagher. (2020). Multi-Gene Prognostic Signatures and Prediction of Pathological Complete Response to Neoadjuvant Chemotherapy in ER-Positive, HER2-Negative Breast Cancer Patients. Cancers. 12(5). 1133–1133. 16 indexed citations

13.

Mazo, Claudia, et al.. (2019). Multi-gene prognostic signatures and prediction of pathological complete response of ER-Positive HER2-negative breast cancer patients to neo-adjuvant chemotherapy. Annals of Oncology. 30. v86–v86. 3 indexed citations

14.

Mazo, Claudia, et al.. (2018). In Silico Approach for Immunohistochemical Evaluation of a Cytoplasmic Marker in Breast Cancer. Cancers. 10(12). 517–517. 5 indexed citations

15.

Mazo, Claudia, José Bernal, María Trujillo, & Enrique Alegre. (2018). Transfer learning for classification of cardiovascular tissues in histological images. Computer Methods and Programs in Biomedicine. 165. 69–76. 59 indexed citations

16.

Mazo, Claudia, et al.. (2018). Desarrollo del banco de imágenes histológicas sobre el sistema cardiovascular (BISCAR) [recurso electrónico].

17.

Mazo, Claudia, et al.. (2017). A histological ontology of the human cardiovascular system. Journal of Biomedical Semantics. 8(1). 47–47. 9 indexed citations

18.

Mazo, Claudia, Enrique Alegre, & María Trujillo. (2017). Classification of cardiovascular tissues using LBP based descriptors and a cascade SVM. Computer Methods and Programs in Biomedicine. 147. 1–10. 26 indexed citations

19.

Mazo, Claudia, et al.. (2016). Automatic recognition of fundamental tissues on histology images of the human cardiovascular system. Micron. 89. 1–8. 7 indexed citations

20.

Trujillo, María, et al.. (2015). Automatic Classification of Non-Informative Frames in Colonoscopy Videos. 1 (5 .)–1 (5 .). 3 indexed citations

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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