Magdalini Paschali

557 total citations
13 papers, 114 citations indexed

About

Magdalini Paschali is a scholar working on Radiology, Nuclear Medicine and Imaging, Artificial Intelligence and Computer Vision and Pattern Recognition. According to data from OpenAlex, Magdalini Paschali has authored 13 papers receiving a total of 114 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Radiology, Nuclear Medicine and Imaging, 4 papers in Artificial Intelligence and 3 papers in Computer Vision and Pattern Recognition. Recurrent topics in Magdalini Paschali's 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). Magdalini Paschali is often cited by papers focused on 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). Magdalini Paschali collaborates with scholars based in United States, Germany and South Korea. Magdalini Paschali's 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 and has published in prestigious journals such as Scientific Reports, Radiology and IEEE Access.

In The Last Decade

Magdalini Paschali

10 papers receiving 113 citations

Peers

Magdalini Paschali
Annika Reinke Germany
Tim Adler Germany
Thiranja P. Babarenda Gamage New Zealand
Yinzhe Wu United Kingdom
Bishesh Khanal United Kingdom
A Freitas Portugal
Sekeun Kim United States
Yunhe Gao United States
Annika Reinke Germany
Magdalini Paschali
Citations per year, relative to Magdalini Paschali Magdalini Paschali (= 1×) peers Annika Reinke

Countries citing papers authored by Magdalini Paschali

Since Specialization
Citations

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

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

13 of 13 papers shown
1.
Paschali, Magdalini, Zhihong Chen, Louis Blankemeier, et al.. (2025). Foundation Models in Radiology: What, How, Why, and Why Not. Radiology. 314(2). e240597–e240597. 17 indexed citations
2.
Fang, Zhongnan, Andrew Johnston, Magdalini Paschali, et al.. (2025). Automated real-time assessment of intracranial hemorrhage detection AI using an ensembled monitoring model (EMM). npj Digital Medicine. 8(1). 608–608.
3.
Larson, David B., et al.. (2025). Assessing Completeness of Clinical Histories Accompanying Imaging Orders Using Adapted Open-Source and Closed-Source Large Language Models. Radiology. 314(2). e241051–e241051. 5 indexed citations
4.
Zhao, Qingyu, Magdalini Paschali, Fiona C. Baker, et al.. (2024). Identifying high school risk factors that forecast heavy drinking onset in understudied young adults. Developmental Cognitive Neuroscience. 68. 101413–101413. 1 indexed citations
5.
Paschali, Magdalini, Yu Jiang, Shepard Siegel, et al.. (2024). Spectral Graph Sample Weighting for Interpretable Sub-cohort Analysis in Predictive Models for Neuroimaging. Lecture notes in computer science. 15155. 24–34.
6.
Paschali, Magdalini, Egon Burian, Marcus R. Makowski, et al.. (2023). Multimodal graph attention network for COVID-19 outcome prediction. Scientific Reports. 13(1). 19539–19539. 17 indexed citations
7.
Kim, Seong Tae, Magdalini Paschali, Egon Burian, et al.. (2023). Interactive Segmentation for COVID-19 Infection Quantification on Longitudinal CT Scans. IEEE Access. 11. 77596–77607. 2 indexed citations
8.
Simson, Walter, et al.. (2023). Investigating pulse-echo sound speed estimation in breast ultrasound with deep learning. Ultrasonics. 137. 107179–107179. 15 indexed citations
9.
Paschali, Magdalini, Qingyu Zhao, Ehsan Adeli, & Kilian M. Pohl. (2022). Bridging the Gap Between Deep Learning and Hypothesis-Driven Analysis via Permutation Testing. Lecture notes in computer science. 13564. 13–23. 4 indexed citations
10.
Paschali, Magdalini, Orsolya Kiss, Qingyu Zhao, et al.. (2022). Detecting negative valence symptoms in adolescents based on longitudinal self-reports and behavioral assessments. Journal of Affective Disorders. 312. 30–38. 4 indexed citations
11.
Paschali, Magdalini, et al.. (2020). Ultrasound-Guided Robotic Navigation with Deep Reinforcement Learning. 5534–5541. 33 indexed citations
12.
Simson, Walter, Magdalini Paschali, Nassir Navab, & Guillaume Zahnd. (2018). Deep Learning Beamforming for Sub-Sampled Ultrasound Data. 1–4. 16 indexed citations
13.
Paschali, Magdalini, et al.. (2018). Dual-user interaction in virtual environment towards robotic construction of masonry systems. 176–183.

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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2026