Mara Graziani

541 total citations
20 papers, 172 citations indexed

About

Mara Graziani is a scholar working on Artificial Intelligence, Radiology, Nuclear Medicine and Imaging and Computer Vision and Pattern Recognition. According to data from OpenAlex, Mara Graziani has authored 20 papers receiving a total of 172 indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Artificial Intelligence, 6 papers in Radiology, Nuclear Medicine and Imaging and 5 papers in Computer Vision and Pattern Recognition. Recurrent topics in Mara Graziani's work include AI in cancer detection (7 papers), Explainable Artificial Intelligence (XAI) (5 papers) and Cell Image Analysis Techniques (5 papers). Mara Graziani is often cited by papers focused on AI in cancer detection (7 papers), Explainable Artificial Intelligence (XAI) (5 papers) and Cell Image Analysis Techniques (5 papers). Mara Graziani collaborates with scholars based in Switzerland, United States and Netherlands. Mara Graziani's co-authors include Henning Müller, Vincent Andrearczyk, Adrien Depeursinge, Pedro Henriques Abreu, Rahul Nair, Valeria Pulignano, Tobias Blanke, Wessel Reijers, Davide Calvaresi and John O. Prior and has published in prestigious journals such as Nature Communications, SHILAP Revista de lepidopterología and Science Advances.

In The Last Decade

Mara Graziani

16 papers receiving 168 citations

Peers

Mara Graziani
Comparison fields: 5 of 70
  • Artificial Intelligence 98
  • Radiology, Nuclear Medicine and Imaging 49
  • Health Informatics 31
  • Computer Vision and Pattern Recognition 20
  • Biomedical Engineering 17
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Citations per field, relative to Mara Graziani
Mara Graziani · 1×
Citations per year, relative to Mara Graziani
Mara Graziani · 1×

Countries citing papers authored by Mara Graziani

Since Specialization
Citations

This map shows the geographic impact of Mara Graziani'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 Mara Graziani with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mara Graziani more than expected).

Fields of papers citing papers by Mara Graziani

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Mara Graziani. 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 Mara Graziani. The network helps show where Mara Graziani may publish in the future.

Co-authorship network of co-authors of Mara Graziani

This figure shows the co-authorship network connecting the top 25 collaborators of Mara Graziani. A scholar is included among the top collaborators of Mara Graziani 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 Mara Graziani. Mara Graziani is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
# Work Indexed citations
1 1
2 0
3 35
4 0
5 0
6 4
7 2
8 4
9 65
10 13
11 4
12 4
13 5
14
Visualizing and Interpreting Feature Reuse of Pretrained CNNs for Histopathology
9
15 0
16 2
17 11
18
Visual interpretability for patch-based classification of breast cancer histopathology images
1
19 11
20 1

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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