Magdalini Paschali
- Radiology, Nuclear Medicine and Imaging
- Biomedical Engineering
- Artificial Intelligence
- Computer Vision and Pattern Recognition
- Health Informatics top 10%
- Co-authors
- Nassir NavabWalter SimsonEmad FatemizadehGuillaume ZahndJeremy DahlZhihong ChenEgon BurianQingyu Zhao
- Topics
- Radiomics and Machine Learning in Medical Imaging (3 papers)Artificial Intelligence in Healthcare and Education (3 papers)Robotics and Sensor-Based Localization (2 papers)
- Partner nations
- United StatesGermanySouth Korea
In The Last Decade
Magdalini Paschali
10 papers receiving 113 citations
Peers
Comparison fields: 5 of 45
- Radiology, Nuclear Medicine and Imaging 58
- Biomedical Engineering 43
- Artificial Intelligence 25
- Computer Vision and Pattern Recognition 17
- Health Informatics 17
Countries citing papers authored by Magdalini Paschali
This map shows the geographic impact of Magdalini Paschali'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 Magdalini Paschali with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Magdalini Paschali more than expected).
Fields of papers citing papers by Magdalini Paschali
This network shows the impact of papers produced by Magdalini Paschali. 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 Magdalini Paschali. The network helps show where Magdalini Paschali may publish in the future.
Co-authorship network of co-authors of Magdalini Paschali
This figure shows the co-authorship network connecting the top 25 collaborators of Magdalini Paschali. A scholar is included among the top collaborators of Magdalini Paschali 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 Magdalini Paschali. Magdalini Paschali is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 17 | |
| 2 | 0 | |
| 3 | 5 | |
| 4 | 1 | |
| 5 | 0 | |
| 6 | 17 | |
| 7 | 2 | |
| 8 | 15 | |
| 9 | 4 | |
| 10 | 4 | |
| 11 | 33 | |
| 12 | 16 | |
| 13 | Dual-user interaction in virtual environment towards robotic construction of masonry systems | 0 |
About Magdalini Paschali
Magdalini Paschali is a scholar working on Health Informatics, Radiology, Nuclear Medicine and Imaging and Geology, having authored 13 papers that have together received 114 indexed citations. Recurring topics across this work include Radiomics and Machine Learning in Medical Imaging (3 papers), Artificial Intelligence in Healthcare and Education (3 papers) and Robotics and Sensor-Based Localization (2 papers). The work is most often cited by research in Health Informatics (17 citations), Radiology, Nuclear Medicine and Imaging (58 citations) and Biomedical Engineering (43 citations). Magdalini Paschali has collaborated with scholars based in United States, Germany and South Korea. Frequent co-authors include Nassir Navab, Walter Simson, Emad Fatemizadeh, Guillaume Zahnd, Jeremy Dahl, Zhihong Chen, Egon Burian, Qingyu Zhao, Marcus R. Makowski and Curtis P. Langlotz. Their work appears in journals such as Scientific Reports, Radiology and IEEE Access.
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.